DOCSLIB.ORG

Refactoring Has Proven Its Value in a Wide Range of Development

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Refactoring Has Proven Its Value in a Wide Range of Development Refactoring Databases: Evolutionary Database Design By Scott W. Ambler, Pramod J. Sadalage ............................................... Publisher: Addison Wesley Professional Pub Date: March 06, 2006 Print ISBN-10: 0-321-29353-3 Print ISBN-13: 978-0-321-29353-4 Pages: 384 Table of Contents | Index Refactoring has proven its value in a wide range of development projectshelping software professionals improve system designs, maintainability, extensibility, and performance. Now, for the first time, leading agile methodologist Scott Ambler and renowned consultant Pramodkumar Sadalage introduce powerful refactoring techniques specifically designed for database systems. Ambler and Sadalage demonstrate how small changes to table structures, data, stored procedures, and triggers can significantly enhance virtually any database designwithout changing semantics. You'll learn how to evolve database schemas in step with source codeand become far more effective in projects relying on iterative, agile methodologies. This comprehensive guide and reference helps you overcome the practical obstacles to refactoring real-world databases by covering every fundamental concept underlying database refactoring. Using start-to-finish examples, the authors walk you through refactoring simple standalone database applications as well as sophisticated multi-application scenarios. You'll master every task involved in refactoring database schemas, and discover best practices for deploying refactorings in even the most complex production environments. The second half of this book systematically covers five major categories of database refactorings. You'll learn how to use refactoring to enhance database structure, data quality, and referential integrity; and how to refactor both architectures and methods. This book provides an extensive set of examples built with Oracle and Java and easily adaptable for other languages, such as C#, C++, or VB.NET, and other databases, such as DB2, SQL Server, MySQL, and Sybase. Using this book's techniques and examples, you can reduce waste, rework, risk, and costand build database systems capable of evolving smoothly, far into the future. Refactoring Databases: Evolutionary Database Design By Scott W. Ambler, Pramod J. Sadalage ............................................... Publisher: Addison Wesley Professional Pub Date: March 06, 2006 Print ISBN-10: 0-321-29353-3 Print ISBN-13: 978-0-321-29353-4 Pages: 384 Table of Contents | Index Copyright Praise for Refactoring Databases The Addison-Wesley Signature Series The Addison-Wesley Signature Series About the Authors Forewords Preface Why Evolutionary Database Development? Agility in a Nutshell How to Read This Book About the Cover Acknowledgments Chapter 1. Evolutionary Database Development Section 1.1. Database Refactoring Section 1.2. Evolutionary Data Modeling Section 1.3. Database Regression Testing Section 1.4. Configuration Management of Database Artifacts Section 1.5. Developer Sandboxes Section 1.6. Impediments to Evolutionary Database Development Techniques Section 1.7. What You Have Learned Chapter 2. Database Refactoring Section 2.1. Code Refactoring Section 2.2. Database Refactoring Section 2.3. Categories of Database Refactorings Section 2.4. Database Smells Section 2.5. How Database Refactoring Fits In Section 2.6. Making It Easier to Refactor Your Database Schema Section 2.7. What You Have Learned Chapter 3. The Process of Database Refactoring Section 3.1. Verify That a Database Refactoring Is Appropriate Section 3.2. Choose the Most Appropriate Database Refactoring Section 3.3. Deprecate the Original Database Schema Section 3.4. Test Before, During, and After Section 3.5. Modify the Database Schema Section 3.6. Migrate the Source Data Section 3.7. Refactor External Access Program(s) Section 3.8. Run Your Regression Tests Section 3.9. Version Control Your Work Section 3.10. Announce the Refactoring Section 3.11. What You Have Learned Chapter 4. Deploying into Production Section 4.1. Effectively Deploying Between Sandboxes Section 4.2. Applying Bundles of Database Refactorings Section 4.3. Scheduling Deployment Windows Section 4.4. Deploying Your System Section 4.5. Removing Deprecated Schema Section 4.6. What You Have Learned Chapter 5. Database Refactoring Strategies Section 5.1. Smaller Changes Are Easier to Apply Section 5.2. Uniquely Identify Individual Refactorings Section 5.3. Implement a Large Change by Many Small Ones Section 5.4. Have a Database Configuration Table Section 5.5. Prefer Triggers over Views or Batch Synchronization Section 5.6. Choose a Sufficient Transition Period Section 5.7. Simplify Your Database Change Control Board (CCB) Strategy Section 5.8. Simplify Negotiations with Other Teams Section 5.9. Encapsulate Database Access Section 5.10. Be Able to Easily Set Up a Database Environment Section 5.11. Do Not Duplicate SQL Section 5.12. Put Database Assets Under Change Control Section 5.13. Beware of Politics Section 5.14. What You Have Learned Online Resources Chapter 6. Structural Refactorings Common Issues When Implementing Structural Refactorings Drop Column Drop Table Drop View Introduce Calculated Column Introduce Surrogate Key Merge Columns Merge Tables Move Column Rename Column Rename Table Rename View Replace LOB With Table Replace Column Replace One-To-Many With Associative Table Replace Surrogate Key With Natural Key Split Column Split Table Chapter 7. Data Quality Refactorings Common Issues When Implementing Data Quality Refactorings Add Lookup Table Apply Standard Codes Apply Standard Type Consolidate Key Strategy Drop Column Constraint Drop Default Value Drop Non-Nullable Introduce Column Constraint Introduce Common Format Introduce Default Value Make Column Non-Nullable Move Data Replace Type Code With Property Flags Chapter 8. Referential Integrity Refactorings Add Foreign Key Constraint Add Trigger For Calculated Column Access Program Update Mechanics Drop Foreign Key Constraint Introduce Cascading Delete Introduce Hard Delete Introduce Soft Delete Introduce Trigger For History Chapter 9. Architectural Refactorings Add CRUD Methods Add Mirror Table Add Read Method Encapsulate Table With View Introduce Calculation Method Introduce Index Introduce Read-Only Table Migrate Method From Database Migrate Method To Database Replace Method(s) With View Replace View With Method(s) Use Official Data Source Chapter 10. Method Refactorings Section 10.1. Interface Changing Refactorings Section 10.2. Internal Refactorings Chapter 11. Transformations Insert Data Introduce New Column Introduce New Table Introduce View Update Data The UML Data Modeling Notation Glossary References and Recommended Reading List of Refactorings and Transformations Index Copyright Many of the designations used by manufacturers and sellers to distinguish their products are claimed as trademarks. Where those designations appear in this book, and the publisher was aware of a trademark claim, the designations have been printed with initial capital letters or in all capitals. The authors and publisher have taken care in the preparation of this book, but make no expressed or implied warranty of any kind and assume no responsibility for errors or omissions. No liability is assumed for incidental or consequential damages in connection with or arising out of the use of the information or programs contained herein. The publisher offers excellent discounts on this book when ordered in quantity for bulk purchases or special sales, which may include electronic versions and/or custom covers and content particular to your business, training goals, marketing focus, and branding interests. For more information, please contact: U.S. Corporate and Government Sales (800) 382-3419 [email protected] For sales outside the United States, please contact: International Sales [email protected] Visit us on the Web: www.awprofessional.com Library of Congress Cataloging-in-Publication Data Ambler, Scott W., 1966- Refactoring databases : evolutionary database design / Scott W. Ambler and Pramod J. Sadalage. p. cm. Includes index. ISBN 0-321-29353- 3 (hardback : alk. paper) 1. Database design. 2. Computer softwareDevelopment. 3. Evolutionary programming (Computer science) I. Sadalage, Pramod J. II. Title. QA76.9.D26A52 2006 005.74dc22 2005031959 Copyright © 2006 Scott W. Ambler and Pramodkumar J. Sadalage All rights reserved. Printed in the United States of America. This publication is protected by copyright, and permission must be obtained from the publisher prior to any prohibited reproduction, storage in a retrieval system, or transmission in any form or by any means, electronic, mechanical, photocopying, recording, or likewise. For information regarding permissions, write to: Pearson Education, Inc. Rights and Contracts Department 75 Arlington Street, Suite 300 Boston, MA 02116 Fax: (617) 848-7047 Text printed in the United States on recycled paper at R. R. Donnelley in Crawfordsville, Indiana. First printing, March 2006 Dedication Scott: For Beverley, my lovely new bride. Pramod: To the women I love most, Rupali and our daughter, Arula. Praise for Refactoring Databases "This groundbreaking book finally reveals why database schemas need not be difficult to change, why data need not be difficult to migrate, and why database professionals need not be overburdened by change requests from customers and developers. Evolutionary design is at the heart of agility. Ambler and Sadalage have now shown the world how to evolve agile databases. Bravo!" Joshua Kerievsky,
Load more

Recommended publications
  • Ssql-Schema-Comparer: Support of Multi-Language Refactoring With
    2013 IEEE 13th International Working Conference on Source Code Analysis and Manipulation (SCAM) sql-schema-comparer: Support of Multi-Language Refactoring with Relational Databases Hagen Schink Institute of Technical and Business Information Systems Otto-von-Guericke-University Magdeburg, Germany [email protected] Abstract—Refactoring is a method to change a source-code’s State-of-the-art IDEs provide information about syntactical structure without modifying its semantics and was first intro- changes or errors before integration or runtime tests take duced for object-oriented code. Since then refactorings were effect. Hence, the information can enable software developers defined for relational databases too. But database refactorings must be treated differently because a database schema’s structure to recognize and correct syntactic and some semantic errors defines semantics used by other applications to access the data already during development. We argue that information about in the schema. Thus, many database refactorings may break syntactical changes in database schemes can ease the problems interaction with other applications if not treated appropriately. of database refactoring. We discuss problems of database refactoring in regard to Java In the following we first present two techniques for ac- code and present sql-schema-comparer, a library to detect refac- torings of database schemes. The sql-schema-comparer library cessing a relational database with the programming language is our first step to more advanced tools supporting developers in Java. Then, we describe how database refactoring affects their database refactoring efforts. database access from Java. In Sec. III we give a more general explanation of problems resulting from database refactorings.
    [Show full text]
  • Automated Testing of Database Schema Migrations
    DEGREE PROJECT IN COMPUTER SCIENCE AND ENGINEERING, SECOND CYCLE, 30 CREDITS STOCKHOLM, SWEDEN 2019 Automated Testing of Database Schema Migrations PETER JONSSON KTH ROYAL INSTITUTE OF TECHNOLOGY SCHOOL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCE Automated Testing of Database Schema Migrations PETER JONSSON Master in Computer Science Date: June 28, 2019 Supervisor: Johan Gustavsson Examiner: Elena Troubitsyna School of Electrical Engineering and Computer Science Host company: The Swedish Police Authority Swedish title: Automatiserad testning av databasschemaförändringar iii Abstract Modern applications use databases, and the majority of them are relational databases, which use schemas to impose data integrity constraints. As appli- cations change, so do their databases. Database schemas are changed using migrations. Certain conditions can result in migrations failing in production environments, leading to a broken database state and testing can be problem- atic without accessing production data which can be sensitive. Two migration validation methods were proposed and implemented to au- tomatically reject invalid migrations that are not compatible with the database state. The methods were based on, and compared to, a default method that used Liquibase to structure and perform migrations. The assertion method used knowledge of what a valid state would look like to generate pre-conditions from assertions to verify that the database’s state matched expectations and that the migrations were compatible with a database’s state prior to migra- tion. The schema method, used a copy of the production database’s schema to perform migrations on an empty database in order to test the compatibility of the old and new schemas. 108 test cases consisting of a migration and a database state were used to test all methods.
    [Show full text]
  • LESSQL: an Approach to Deal with Database Schema Changes in Continuous Deployment / Ariel Antony Afonso
    LESSQL: AN APPROACH TO DEAL WITH DATABASE SCHEMA EVOLUTION IN CONTINUOUS DEPLOYMENT ARIEL ANTONY AFONSO LESSQL: AN APPROACH TO DEAL WITH DATABASE SCHEMA EVOLUTION IN CONTINUOUS DEPLOYMENT Dissertation presented to the Graduate Program in Informatics of the Universidade Federal do Amazonas in partial fulfillment of the requirements for the degree of Master in Informatics. Advisor: Altigran Soares da Silva Manaus April 2020 Ficha Catalográfica Ficha catalográfica elaborada automaticamente de acordo com os dados fornecidos pelo(a) autor(a). Afonso, Ariel Antony A257l LESSQL: An approach to deal with Database Schema Changes in Continuous Deployment / Ariel Antony Afonso . 2020 55 f.: il. color; 31 cm. Orientador: Altigran Soares da Silva Dissertação (Ciência da Computação) - Universidade Federal do Amazonas. 1. schema changes. 2. continuous deployment. 3. database decay. 4. query language. I. Silva, Altigran Soares da. II. Universidade Federal do Amazonas III. Título PODER EXECUTIVO MINISTÉRIO DA EDUCAÇÃO INSTITUTO DE COMPUTAÇÃO PROGRAMA DE PÓS-GRADUAÇÃO EM INFORMÁTICA FOLHA DE APROVAÇÃO " " Dissertação de Mestrado defendida e aprovada pela banca examinadora constituída pelos Professores: - PRESIDENTE Prof - MEMBRO INTERNO - MEMBRO EXTERNO - MEMBRO EXTERNO Manaus, de de 20 Av. Rodrigo Otávio, 6.200 - Campus Universitário Senador Arthur Virgílio Filho - CEP 690-00 - Manaus, AM, Brasil Tel. (092) 3305 1193 E-mail: [email protected] www.ppgi.ufam.edu.br “Embora ninguém possa voltar atrás e fazer um novo começo, qualquer um pode começar agora e fazer um novo fim.” (Chico Xavier) vii Abstract The adoption of Continuous Deployment (CD) aims at allowing software systems to quickly evolve to accommodate new features. However, structural changes to the database schema are frequent and may incur in systems’ services downtime.
    [Show full text]
  • Devops for the Database
    eBOOK DevOps for the Database By Baron Schwartz E-BOOK: DEVOPS FOR THE DATABASE Table of Contents Meet the Author 1 Introduction 2 Who This Book Is For 3 Database DevOps Stories 3 What Is DevOps 6 Database DevOps Capabilities 8 What Kinds of Companies Can Apply DevOps to the Database? 12 Benefits of DevOps for the Database 14 Why Is it Hard to Apply DevOps to the Database? 15 You Can’t Buy DevOps 25 Achieving Continuous Delivery With Databases 27 Schema as Code for Monoliths and Microservices 29 Automating Database Migrations 31 Loosening the Application/Database Coupling 40 Improving Database Observability 44 Democratizing Database Knowledge and Skill 50 Realigning Software Development Teams 55 The Importance of the Second Age of DevOps 60 Your Journey Towards Database DevOps 63 Three Steps on the Journey 68 Acknowledgments 69 E-BOOK: DEVOPS FOR THE DATABASE Meet the Author Baron Schwartz Baron, the founder of VividCortex, is a performance and scalability expert who participates in various database, open-source, and distributed systems communities. He has helped build and scale many large, high-traffic services for Fortune 1000 clients. He has written several books, including O’Reilly’s best-selling High Performance MySQL. Baron has a Computer Science degree from the University of Virginia. page 1 E-BOOK: DEVOPS FOR THE DATABASE Introduction When it comes to the database, some teams innovate faster, break things less, make more money, and have happier humans. I tried to discover what distinguishes the high and low performers. Then, I struggled to find words for it. Eventually, I realized it’s DevOps.
    [Show full text]
  • Enhancing Database-Centric Web Applications Through Informed Code Generation
    Utah State University DigitalCommons@USU All Graduate Theses and Dissertations Graduate Studies 8-2017 Database Auto Awesome: Enhancing Database-Centric Web Applications through Informed Code Generation Jonathan Adams Utah State University Follow this and additional works at: https://digitalcommons.usu.edu/etd Part of the Other Computer Sciences Commons Recommended Citation Adams, Jonathan, "Database Auto Awesome: Enhancing Database-Centric Web Applications through Informed Code Generation" (2017). All Graduate Theses and Dissertations. 6265. https://digitalcommons.usu.edu/etd/6265 This Thesis is brought to you for free and open access by the Graduate Studies at DigitalCommons@USU. It has been accepted for inclusion in All Graduate Theses and Dissertations by an authorized administrator of DigitalCommons@USU. For more information, please contact [email protected]. DATABASE AUTO AWESOME: ENHANCING DATABASE-CENTRIC WEB APPLICATIONS THROUGH INFORMED CODE GENERATION by Jonathan Adams A thesis submitted in partial fulfillment of the requirements for the degree of MASTER OF SCIENCE in Computer Science Approved: Curtis Dyreson, Ph.D. Minghui Jiang, Ph.D. Major Professor Committee Member Kyumin Lee, Ph.D. Mark R. McLellan, Ph.D. Committee Member Vice President for Research and Dean of the School of Graduate Studies UTAH STATE UNIVERSITY Logan, Utah 2017 ii Copyright c Jonathan Adams 2017 All Rights Reserved iii ABSTRACT Database Auto Awesome: Enhancing Database-Centric Web Applications through Informed Code Generation by Jonathan Adams, Master of Science Utah State University, 2017 Major Professor: Curtis Dyreson, Ph.D. Department: Computer Science Database Auto Awesome is an approach to enhancing in-situ, web-based, relational database applications through informed code generation.
    [Show full text]
  • Artificial Intelligence and Knowledge Engineering
    AUTOMATING SUPPORT FOR REFACTORING SQL DATABASES Jyrki Nummenmaa, Ari Seppi, Peter Thanisch University of Tampere, Department of Computer Sciences, 33014 University of Tampere, Tampere, Finland, [email protected], [email protected], [email protected] Abstract. We present a method to automate at least partly the operations needed to refactor an SQL database in the case where a new schema is designed for an existing SQL database that contains data. We base our database refactoring method on intuitive database design operations, such as normalize and denormalize. Keywords: SQL databases, database maintenance, database refactoring, database evolution. 1 Introduction Relational database design is a much studied and classical problem. Often the relational database model is based on some higher•level conceptual model. Over time, the concepts and the conceptual level model change and there is a need to update the database. There is solid research on how, for example, the database schema evolution should be designed based on an ER schema. However, although there is quite a lot of work on schema evolution, we could not find solid research on how an existing relational (or SQL) database should be re•organised, when there is a need to change the database schema. Our conjecture is that this topic has been neglected because researchers were of the opinion that a viable solution to the problem was to redesign the schema at the entity•relationship model level and to migrate the data to the new schema. However, in many production environments, such an upheaval would not be practical. The practical significance of the approach that we propose derives from the fact that schema changes continue to be necessary even after the database has been populated and is in the production environment.
    [Show full text]
  • Database Schema Software Open Source
    Database Schema Software Open Source Unsubstantiated Serge whammed his empiricists aquaplaned digestedly. Ambidextrous and wordless Tomkin uptearing, but Freemon biyearly inches her cookhouse. Verisimilar and covariant Levon always incarcerates wofully and bethinking his filth. Sybase and relationships between the open source software requirements, pretty diagrams is quite Pg admin is what source and rod do some basic diagram stuff 4 share can Save. Toad's database modeling tools simplify design maintenance and documentation at a price your organization can afford Download Free or Buy. Yes no server software to install and waiter service to eager to. Opensource Collaborative Environment then Database Management Host a web version of similar tool whose team commitment to databases or affirm a software package of the. When playing open SQLite Database Browser, ADO. It allows you to do entity relationship diagram. This mapping relates the external schema with the logical schema. Directus ships with database schema control tools require a visual form so long as a single purpose of open the. Is schema same exact database? It does generate or include binary log file and log positions which is very helpful book you setup the fishing destination platform to assert as a replica of exercise current item and production environment. Modern, but intractable, and optimize your processes. Allow you carefully save and drill your diagrams online. 15 Best Free Database Software that poke Your booze Better. Melbourne and garlic a candle at both RMIT University, analyze, can be expensive. Learn therefore about Calibrum. The Liquibase product portfolio is designed with speed, patches, eventually becoming available refer the entire cluster.
    [Show full text]
  • Refactoring Rules for Graph Databases Regras De
    i ADRIANE DE MARTINI FONSECA REFACTORING RULES FOR GRAPH DATABASES REGRAS DE REFATORAÇÃO PARA BANCO DE DADOS BASEADO EM GRAFOS LIMEIRA 2015 ii iii UNIVERSIDADE ESTADUAL DE CAMPINAS Faculdade de Tecnologia ADRIANE DE MARTINI FONSECA REFACTORING RULES FOR GRAPH DATABASES REGRAS DE REFATORAÇÃO PARA BANCO DE DADOS BASEADO EM GRAFOS Dissertation presented to the School of Technology of the University of Campinas in partial fulfillment of the requirements for the degree of Master, in the area of Technology Dissertação apresentada à Faculdade de Tecnologia da Universidade Estadual de Campinas como parte dos requisitos exigidos para a obtenção do título de Mestra em Tecnologia, na Área de Tecnologia e Inovação Supervisor/Orientador: Prof. Dr. Luiz Camolesi Jr. ESTE EXEMPLAR CORRESPONDE À VERSÃO FINAL DISSERTAÇÃO DEFENDIDA PELA ALUNA ADRIANE DE MARTINI FONSECA, E ORIENTADA PELO PROF. DR. LUIZ CAMOLESI JR. _____________________________ LIMEIRA 2015 iv v vi vii ABSTRACT The information produced nowadays does not stop growing in volume and complexity, representing a technological challenge which demands more than the relational model for databases can currently offer. This situation stimulates the use of different forms of storage, such as Graph Databases. Current Graph Databases allow automatic database evolution, but do not provide adequate resources for the information organization. This is mostly left under the responsibility of the applications which access the database, compromising the data integrity and reliability. The goal of this work is the definition of refactoring rules to support the management of the evolution of Graph Databases. The rules presented in this document are adaptations and extensions of the existent refactoring rules for relational databases to meet the requirements of the Graph Databases features.
    [Show full text]
  • Database Refactoring with Liquibase
    Database Refactoring with Liquibase Michael Le Feuvre, OnBelay Consulting Agenda • What is Database refactoring • Introducing Liquibase • Liquibase example • Questions OnBelay Consulting 2 Database Refactoring Evolutionary change OnBelay Consulting 3 Traditional approach • Traditional approach to changing the database schema. • Make an appointment to see the DBA. • Plead that you want to add a column to an existing table • DBA considers your request • Decides to grant it but first must update the ER diagram in a horribly expensive Database Architecture and Design tool that maintains a logical data model. The model is then rendered in to a physical model. Great for wall charts. • DBA generates or hand-codes the database changes into SQL scripts. • DBA then updates each database directly that requires the changes. OnBelay Consulting 4 Consequences of traditional approach • Because the overhead in the traditional process is so onerous, many organizations required that database design be done up front so that the database was “ready” for programmers to use. • Database artifacts may not be in source control. • If database objects are in source control they aren’t necessarily in the same repository as the application source code. application code changes and database changes are not committed together in the same commit. • The above process is entirely antithetical to an Agile development process and since the database requirements must be known in advance of starting development • Most organizations manage database changes somewhere between traditional and database refactoring. OnBelay Consulting 5 Database refactoring • Based on the concept of refactoring popularized by Martin Fowler: • described as a “refactoring as a small change to your source code that improves its design without changing its semantics.” (Refactoring, Martin, James, 1999) • Evolutionary approaches to database maintenance have been discussed since the 2000’s.
    [Show full text]
  • Test-L[Iuen Lleuelopment Ol Belational Llatabases
    I0$l-[[ill0[ ll 0 ll s I ll I lll 0 ll I . o . Test-l[iuen lleuelopment ol Belational llatabases Scott W. Ambler, rrM n test-first development, developers formulate and implement a de- lmplemenling tailed design iteratively one test at a time.1,2 Test-driven development lesl-driven (also called test-driven design) combines TFD with refactoring,3 dolshuse design wherein developers make small changes (refactorings) to improve involves dolobose code design without changing the code's semantics.'Sfhen developers decide refocloring, to use TDD to implement a new feature, they must first ask whether the cur- regression lesling, rent design is the easiest possible design to enable the feature's addition. If ond conlinuous so, they implement the feature via TFD. If not, because sometimes you'll write a developer test inlegrolion. they first refactor the code, then use TFD. In that specifies application code behavior, while Although technicolly the behavior-driven deveiopment4 approach to other times it will specify database behavior. naming and TDDD is important for several reasons. slroightforword, TDD, the conventions terminology make the developer's primary goal explicit: to First, a1l of application TDD's benefits apply to TDDD involves specify, rather than validate, the system. TDDD: you can take small, safe steps; refactor- culturol chollenges Test-driven database design applies TDD to ing lets you maintain high-quality design database development. In TDDD, developers throughout the life cycle; regression testing lets lhot slow ils implement critical behaviors (including business you detect defects earlier in the li{e cycle; and, odoplion.
    [Show full text]
  • Database Schema Design Best Practices
    Database Schema Design Best Practices Incapacitating Wheeler blubber minutely. Meaningfully squirarchical, Maurits objurgating cyprus and trembling pollutions. Welsh usually dawdles femininely or spoliates diabolically when close-fisted Fredrick chumps concordantly and unrecognisable. The Transaction Item table only has a link to the Product table, which is numerical. GB fully in parallel. The diagram shows these layers together. Data still resides on storage media burdened with the same hardware related caveats. You can then add the primary key from the Categories table to the Products table as a foreign key. In essence, it allows designers to incorporate objects into the familiar table structure. If a human being could not pick which row they want from a table without knowledge of the surrogate key, then you need to reconsider your design. This is the contrast between planned and evolutionary design. That comes up as attributes attached to design database schema best practices to recover the buffer to. In this guide, we will learn what is an instance and schema in DBMS. Conversation applications and systems development suite for virtual agents. While you consider suspending a warehouse to save credits, remember that you would be letting go of the data in the cache too. From an ER Schema to a Relational. We can transfer objects to different schemas, as well. If you must merge all country data then a better way would be a table of countries having fields of country code, currency code, and currency name, and then provide indices on both code fields. PKs, instead, to use integer PK makes things a lot easier.
    [Show full text]
  • Database Refactoring to Increase/Retrieve Information from Precision Agriculture Information System
    Database Refactoring to Increase/Retrieve Information From Precision Agriculture Information System Marcia Beatriz Pereira Domingues, Jorge Rady Almeira Junior, Wilian Franca Costa, and Antonio Saraiva Department of Electrical Engineering Polytechnic School, University of Sao Paulo, Sao Paulo, Brazil [email protected], [email protected], [email protected], [email protected] ABSTRACT Precision Agriculture (PA) Information Systems improve farm management helping to make the best decisions based on all available information, keeping, controlling, and optimizing resources, returns, and preserving the environment. These systems need to archive, retrieve, and process large amounts of data from many different farms for future analyses. It has to be done without neglecting aspects of entity-relationship model (ER model) at the same time describing all crop cycle’s stages. With minor changes in the database schema, the performance of geospatial queries can be improved by refactoring tasks in the literature related to Agile Software Development. A refactoring represents structural, architectural, integrity or data quality change that preserves the system functionalities. As a case study, a PA Information Portal System database that dynamically generates models based on input data was created to represent the relations of input data generated for a Spatial Data Infrastructure used in a PA. In this context, we redesigned this database introducing refactoring techniques in order to improve PA queries performance. Keywords: Precision Agriculture, Database Refactoring, Evolutionary Databases, Spatial Databases, Query Performance, Brazil. 1. INTRODUCTION Precision Agriculture (PA) Information Systems improve farm management helping to make the best decisions based on all available information, keeping, controlling, and optimizing resources, returns, and preserving the environment.
    [Show full text]