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If you've not programmed with Transact-SQL, this book is for you.It begins with an overview of SQL Server query operations and tools used with T-SQL, and covers both the 2005 and 2008 releases of SQL Server query tools and the query editor. The book then moves to show you how to design and build applications of increasing complexity. Other important tasks covered include full text indexing, optimizing query performance, and application design and security considerations. The companion website also provides all of the code examples from the book.
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Contents
Introduction
Chapter 1: Introducing T-SQL and Data Management Systems
T-SQL Language
SQL Server as a Relational Database Management System
SQL Server and Other Products
Summary
Chapter 2: SQL Server Fundamentals
Who Uses SQL Server?
SQL Server Editions and Features
Semantics
Normalization Rules
Applying Normalization Rules
The Mechanics of Query Processing
The AdventureWorks Databases
Summary
Chapter 3: SQL Server Tools
Common SQL Server Tasks
SQL Server Management Studio
SQL Server Business Intelligence Development Studio
SQL Server Profiler
Database Tuning Advisor
SQL Server Configuration Manager
Command-Line Tools
Writing Queries
Summary
Exercises
Chapter 4: Introducing the T-SQL Language
The Nature of SQL
Where to Begin?
Data Manipulation Language
Data Definition Language
Data Control Language
Summary
Exercises
Chapter 5: Data Retrieval
Storage and Retrieval
The SELECT Statement
Summary
Exercises
Chapter 6: SQL Functions
The Anatomy of a Function
Aggregate Functions
Configuration Variables
Conversion Functions
Cursor Functions and Variables
Date Functions
String Manipulation Functions
Mathematical Functions
Metadata Functions
Ranking Functions
Security Functions
System Functions and Variables
Global System Statistical Variables
Summary
Exercises
Chapter 7: Aggregation and Grouping
To Group or Not to Group
Using Aggregate Functions
Understanding Statistical Functions
Grouping Data
Summary
Exercises
Chapter 8: Multi-Table Queries
Understanding Subqueries and Joins
Summary
Exercises
Chapter 9: Advanced Queries and Scripting
Subqueries
Common Table Expressions
Cursors
Summary
Exercises
Chapter 10: Transactions
Introducing Transactions
Let’s Do CRUD with Data
Explicit Transactions
Summary
Exercises
Chapter 11: Advanced Capabilities
Pivoting Data
Full-Text Queries and Approximation Matching
Microsoft Search Service
Managing and Populating Catalogs
Summary
Exercises
Chapter 12: T-SQL Programming Objects
Views
Stored Procedures
User-Defined Functions
Transaction Management
Summary
Exercises
Chapter 13: Creating and Managing Database Objects
Data Definition Language
IF EXISTS
Securing Database Objects
Summary
Exercises
Chapter 14: Analyzing and Optimizing Query Performance
Data Retrieval
Analyzing Queries
Writing Efficient T-SQL (Best Practices)
Summary
Exercises
Chapter 15: T-SQL in Applications and Reporting
Application Programming Models
Selecting a Model
SQL Server 2008 Reporting Services
Summary
Appendix A: Command Syntax Reference
Appendix B: System Variables and Functions Reference
Appendix C: System Stored Procedure Reference
Appendix D: Information Schema Views Reference
Appendix E: FileStream Objects and Syntax
Appendix F: Answers to Exercises
Index
Beginning T-SQL with Microsoft® SQL Server® 2005 and 2008
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ISBN: 978-0-470-25703-6
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My wife, Sherri, is the reason I do anything meaningful in my life. The rest of it I pretty much come up with on my own. Thank you for your love, support and the occasional knock upside the head.
—Paul Turley
For my wonderful wife, Sarah: Without your constant love and support, I could accomplish nothing. You are truly my best friend.
—Dan Wood
About the Authors
Paul Turley (Vancouver, WA) is a Manager of Specialized Services for Hitachi Consulting Education Services. Paul manages the Business Intelligence training team and teaches classes for companies throughout the world on Microsoft SQL Server technologies. He works with companies to architect and build BI and reporting solutions. He has been developing business database solutions since 1991 for companies like Microsoft, Disney, Nike, and Hewlett-Packard. He has been a Microsoft Certified Trainer since 1996 and holds several industry certifications, including MCTS and MCITP for BI, MCSD, MCDBA, MSF Practitioner, and IT Project+.
Paul has authored and co-authored several books and courses on database, business intelligence, and application development technologies. He is the lead courseware developer for the Hitachi Consulting courses: SQL Server 2008 Business Intelligence Solutions and SQL Server 2008 Reporting Services Solutions. Books include the prior edition of this book, the 2008, 2005 and 2000 editions of Professional SQL Server Reporting Services, Beginning SQL Server 2005 Administration, Beginning Access 2002 VBA, Data Warehousing with SQL Server 2000 Analysis Services, and Professional Access 2000 Programming—all from Wrox. He is also a contributing author for SQL Server 2005 Integration Services Step by Step from Microsoft Press.
Dan Wood (Silverdale, WA) is the senior database administrator for Avalara, a sales tax compliance company, where he both administers and develops database solutions for several enterprise applications that handle global address validation, tax rate calculation, and sales tax remittance for e-commerce and ERP clients. He has been working with SQL Server as a DBA, consultant, and trainer since 1999. Dan was a contributing author on Beginning Transact-SQL with SQL Server 2000 and 2005 and the lead author of Beginning SQL Server Administration, both from Wrox.
Credits
Executive Editor
Robert Elliott
Development Editor
John Sleeva
Technical Editor
David Norton
Production Editor
Daniel Scribner
Copy Editor
Nancy Rapoport
Editorial Manager
Mary Beth Wakefield
Production Manager
Tim Tate
Vice President and Executive Group Publisher
Richard Swadley
Vice President and Executive Publisher
Joseph B. Wikert
Project Coordinator, Cover
Lynsey Stanford
Proofreader
Publication Services, Inc.
Indexer
Robert Swanson
Acknowledgments
This book wouldn’t exist without the hard work and dedication of my coauthor, Dan Wood. Dan’s a good friend, a true professional, a great father and husband - and I hear he’s an okay football coach. Thanks to Bob Elliot and John Sleeva at Wrox who have been incredibly patient and professional with two completely over-committed authors for the past year. DJ Norton did a great job with the technical review. Thanks, DJ, for breaking my code and making more work for me. Thanks to Lance Baldwin and Drew Naukam on Hitachi Consulting’s Microsoft Strategic Alliance team for giving me the space to complete this and the Reporting Services book this year. To all of the amazing people I work with at Hitachi Consulting, thanks for making this such a terrific organization for our clients and a great place to call home.
—Paul Turley
I’d like to thank Paul Turley, who is not only a great friend, but an amazing person, and I appreciate the opportunity to work with him again. Many thanks to our Wrox development editor, John Sleeva, who did an outstanding editing job — not to mention the job he did working with us, which was probably very much like herding cats. Special thanks go to the awesome development team at Avalara for a rewarding and stimulating work environment and for giving me inspiration for many of the examples in this book. Most important, I would like to thank my wonderful wife, Sarah, for all her patience and support as I disappeared for hours at a time and spent many a late night trying to finish the latest chapter. I would also like to thank my kids, Lukas, Tessa, and Caleb, who think it’s cool that Dad is writing a book but would much prefer that I spend time with them.
—Dan Wood
Introduction
Welcome to the world of Transact-Structured Query Language programming with SQL Server 2005 and 2008. Transact-SQL, or T-SQL, is Microsoft Corporation’s powerful implementation of the ANSI standard SQL database query language, which was designed to retrieve, manipulate, and add data to relational database management systems (RDBMS).
You may already have a basic idea of what SQL is used for, but you may not have a good understanding of the concepts behind relational databases and the purpose of SQL. This book will help you build a solid foundation of understanding, beginning with core relational database concepts and continuing to reinforce those concepts with real-world T-SQL query applications.
If you are familiar with relational database concepts but are new to Microsoft SQL Server or the T-SQL language, this book will teach you the basics from the ground up. If you’re familiar with earlier versions of SQL Server, it will get you up to speed on the newest features. And if you know SQL Server 2005, you’ll learn about some exciting new capabilities in SQL Server 2008.
A popular online encyclopedia lists about 800 distinct programming languages in use today. These languages are used to develop different types of applications for different types of computer systems and specialized devices. Needless to say, we have a lot of software in our information-rich society. Programming languages rapidly evolve and come and go, but one of few constants in the industry is that most business applications read, store, and manipulate data — data stored in relational databases. If you use Microsoft SQL Server in any capacity, the need to learn and use T-SQL is inescapable. Amazing things are possible with just a few keystrokes of powerful SQL script.
Indeed, SQL is one of the few standard languages in the industry that doesn’t come and go and has remained constant over the decades. The capabilities of T-SQL expand as features are added to each version of the SQL Server product. The concepts and exercises in this book will help you to understand and use the core language and its latest features.
Who This Book Is For
Information Technology professionals in many different roles use T-SQL. Our goal is to provide a guide and a reference for IT pros across the spectrum of operational database solution design, database application development, and reporting and business intelligence solutions.
Database solution designers will find this book to be a thorough introduction and comprehensive reference for all aspects of database modeling, design, object management, query design, and advanced query concepts.
Application developers who write code to manage and consume SQL Server data will benefit from our thorough coverage of basic data management and simple and advanced query design. Several examples of ready-to-use code are provided to get you started and to continue to support applications with embedded T-SQL queries.
Report designers will find this book to be a go-to reference for report query design. You will build on a thorough introduction to basic query concepts and learn to write efficient queries to support business reports and advanced analytics.
Finally, database administrators who are new to SQL Server will find this book to be an all-inclusive introduction and reference of mainstream topics. This can assist you as you support the efforts of other team members. Beyond the basics of database object management and security concepts, we recommend Beginning SQL Server 2005 Administration and Beginning SQL Server 2008 Administration from Wrox, co-authored in part by the same authors.
What This Book Covers
This book introduces the T-SQL language and its many uses, and serves as a comprehensive guide at a beginner through intermediate level. Our goal in writing this book was to cover all the basics thoroughly and to cover the most common applications of T-SQL at a deeper level. Depending on your role and skill level, this book will serve as a companion to the other Wrox books in the Microsoft SQL Server Beginning and Professional series. Check the back cover of this book for a road map of other complementary books in the Wrox series.
This book will help you to learn:
How T-SQL provides you with the means to create tools for managing databases of different size, scope, and purposeVarious programming techniques that use views, user-defined functions, and stored proceduresWays to optimize query performanceHow to create databases that will be an essential foundation to applications you develop laterHow This Book Is Structured
Each section of this book organizes topics into logical groups so the book can be read cover-to-cover or used as a reference guide for specific topics.
We start with an introduction to the T-SQL language and data management systems, and then continue with the SQL Server product fundamentals. This first section teaches the essentials of the SQL Server product architecture and relational database design principles. This section (Chapters 1–3) concludes with an introduction to the SQL Server administrator and developer tools.
The next section, encompassing Chapters 4 through 9, introduces the T-SQL language and teaches the core components of data retrieval, SQL functions, aggregation and grouping, and multi-table queries. We start with the basics and build on the core structure of the SQL SELECT statement, progressing to advanced forms of SELECT queries.
Chapter 10 introduces transactions and data manipulation. You will learn how the INSERT, UPDATE, and DELETE statements interact with the relational database engine and transaction log to lock and modify data rows with guaranteed consistency. You will not only learn to use correct SQL syntax but will understand how this process works in simple terms.
More advanced topics in the concluding section will teach you to create and manage T-SQL programming objects, including views, functions, and stored procedures. You learn to optimize query performance and use T-SQL in application design, applying the query design basics to real-world business solutions. Chapter 15 contains a complete tutorial on using SQL Server 2008 Reporting Services to visualize data from the T-SQL queries you create.
The book concludes with a comprehensive set of reference appendixes for command syntax, system stored procedures, information schema views, file system commands, and system management commands.
What You Need to Use This Book
The material in this book applies to all editions of Microsoft SQL Server 2005 and 2008. To use all the features discussed, we recommend that you install the Developer Edition, although you can also use the Enterprise, Standard, or Workgroup editions.
SQL Server 2005 Developer Edition or SQL Server 2008 Developer Edition can be installed on a desktop computer running Windows 2000, Windows XP, or Windows Vista. You can also use Windows 2000 Server, Windows Server 2003, or Windows Server 2008 with the Enterprise or Standard edition. The SQL Server client tools must be installed on your desktop computer and the SQL Server relational database server must be installed on either your desktop computer or on a remote server with network connectivity and permission to access.
Consult www.microsoft.com/sql for information about the latest service packs, specific compatibilities, and minimum recommend system requirements.
The examples throughout this book use the following sample databases, which are available to download from Microsoft: the sample database for SQL Server 2005 is called AdventureWorks, and the sample database for SQL Server 2008 is called AdventureWorks2008. Because the structure of these databases differs significantly, separate code samples are provided throughout the book for these two version-specific databases.
An example using the AdventureWorks2008DW database for SQL Server 2008 is also used in Chapter 15.
To download and install these sample databases, browse www.codeplex.com.
Conventions
To help you get the most from the text and keep track of what’s happening, we’ve used a number of conventions throughout the book.
Try It Out
The Try It Out is an exercise you should work through, following the text in the book.
1. They usually consist of a set of steps.
2. Each step has a number.
3. Follow the steps through with your copy of the database.
Boxes like this one hold important, not-to-be forgotten information that is directly relevant to the surrounding text.
Notes, tips, hints, tricks, and asides to the current discussion are offset and placed in italics like this.
As for styles in the text:
We highlight new terms and important words when we introduce them.We show keyboard strokes like this: Ctrl+A.We show filenames, URLs, and code within the text like so: persistence.properties.We present code in two different ways:We use a monofont type with no highlighting for most code examples.
We use gray highlighting to emphasize code that's particularly important in
the present context.
Source Code
As you work through the examples in this book, you may choose either to type in all the code manually or to use the source code files that accompany the book. All the source code used in this book is available for download at www.wrox.com. Once at the site, simply locate the book’s title (either by using the Search box or by using one of the title lists) and click the Download Code link on the book’s detail page to obtain all the source code for the book.
Because many books have similar titles, you may find it easiest to search by ISBN; this book’s ISBN is 978-0-470-25703-6.
Once you download the code, just decompress it with your favorite compression tool. Alternatively, you can go to the main Wrox code download page at www.wrox.com/dynamic/books/download.aspx to see the code available for this book and all other Wrox books.
Errata
We make every effort to ensure that there are no errors in the text or in the code. However, no one is perfect, and mistakes do occur. If you find an error in one of our books, like a spelling mistake or faulty piece of code, we would be very grateful for your feedback. By sending in errata you may save another reader from hours of frustration and at the same time you will be helping us provide even higher quality information.
To find the errata page for this book, go to www.wrox.com and locate the title using the Search box or one of the title lists. Then, on the book details page, click the Book Errata link. On this page you can view all errata that has been submitted for this book and posted by Wrox editors. A complete book list including links to each book’s errata is also available at www.wrox.com/misc-pages/booklist.shtml.
If you don’t spot “your” error on the Book Errata page, go to www.wrox.com/contact/techsupport.shtml and complete the form there to send us the error you have found. We’ll check the information and, if appropriate, post a message to the book’s errata page and fix the problem in subsequent editions of the book.
p2p.wrox.com
For author and peer discussion, join the P2P forums at p2p.wrox.com. The forums are a Web-based system for you to post messages relating to Wrox books and related technologies and interact with other readers and technology users. The forums offer a subscription feature to e-mail you topics of interest of your choosing when new posts are made to the forums. Wrox authors, editors, other industry experts, and your fellow readers are present on these forums.
At http://p2p.wrox.com you will find a number of different forums that will help you not only as you read this book, but also as you develop your own applications. To join the forums, just follow these steps:
1. Go to p2p.wrox.com and click the Register link.
2. Read the terms of use and click Agree.
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You can read messages in the forums without joining P2P but in order to post your own messages, you must join.
Once you join, you can post new messages and respond to messages other users post. You can read messages at any time on the Web. If you would like to have new messages from a particular forum e-mailed to you, click the Subscribe to this Forum icon by the forum name in the forum listing.
For more information about how to use the Wrox P2P, be sure to read the P2P FAQs for answers to questions about how the forum software works as well as many common questions specific to P2P and Wrox books. To read the FAQs, click the FAQ link on any P2P page.
Chapter 1
Introducing T-SQL and Data Management Systems
This first chapter introduces you to some of the fundamentals of the design and architecture of relational databases and presents a brief description of SQL as a language. If you are new to SQL and database technologies, this chapter will provide a foundation to help ensure the rest of the book is as useful as possible. If you are already comfortable with the concepts of relational databases and Microsoft’s implementation, you might want to skip ahead to Chapter 2, “SQL Server Fundamentals,” or Chapter 3, “SQL Server Tools.” Both of these chapters introduce the features and tools in SQL Server 2005 and 2008 and discuss how they are used to write T-SQL.
T-SQL Language
I have mentioned to my colleagues and anyone else who might have been listening that one day I was going to write a version of Parker Brother’s Trivial Pursuit entitled “Trivial Pursuit: Geek Edition.” This section gives you some background on the T-SQL language and provides the information you need to get the orange history wedge on the topic of “Database History” in Trivial Pursuit: Geek Edition.
T-SQL is Microsoft’s implementation of a standard established by the American National Standards Institute (ANSI) for the Structured Query Language (SQL). SQL was first developed by researchers at IBM. They called their first pre-release version of SQL “SEQUEL,” which is a pseudo-acronym for Structured English QUEry Language. The first release version was renamed to SQL, dropping the English part but retaining the pronunciation to identify it with its predecessor. As of the release of SQL Server 2008, several implementations of SQL by different stakeholders are in the database marketplace. As you sojourn through the sometimes mystifying lands of database technology you will undoubtedly encounter these different varieties of SQL. What makes them all similar is the ANSI standard to which IBM, more than any other vendor, adheres to with tenacious rigidity. However, what makes the many implementations of SQL different are the customized programming objects and extensions to the language that make it unique to that particular platform.
Microsoft SQL Server 2008 implements the 2003 ANSI standard. The term “implements” is of significance. T-SQL is not fully compliant with ANSI standards in any of its implementations; neither is Oracle’s P/L SQL, Sybase’s SQLAnywhere, or the open-source MySQL. Each implementation has custom extensions and variations that deviate from the established standard. ANSI has three levels of compliance: Entry, Intermediate, and Full. T-SQL is certified at the entry level of ANSI compliance. If you strictly adhere to the features that are ANSI-compliant, the same code you write for Microsoft SQL Server should work on any ANSI-compliant platform; that’s the theory, anyway. If you find that you are writing cross-platform queries, you will most certainly need to take extra care to ensure that the syntax is perfectly suited for all the platforms it affects. The simple reality of this issue is that very few people will need to write queries to work on multiple database platforms. The standards serve as a guideline to help keep query languages focused on working with data, rather than other forms of programming. This may slow the evolution of relational databases just enough to keep us sane.
Programming Language or Query Language?
T-SQL was not really developed to be a full-fledged programming language. Over the years, the ANSI standard has been expanded to incorporate more and more procedural language elements, but it still lacks the power and flexibility of a true programming language. Antoine, a talented programmer and friend of mine, refers to SQL as “Visual Basic on Quaaludes.” I share this bit of information not because I agree with it, but because I think it is funny. I also think it is indicative of many application developers’ view of this versatile language.
T-SQL was designed with the exclusive purpose of data retrieval and data manipulation. Although T-SQL, like its ANSI sibling, can be used for many programming-like operations, its effectiveness at these tasks varies from excellent to abysmal. That being said, I am still more than happy to call T-SQL a programming language if only to avoid someone calling me a SQL “queryers.” However, the undeniable fact still remains: as a programming language, T-SQL falls short. The good news is that as a data retrieval and set manipulation language it is exceptional. When T-SQL programmers try to use T-SQL like a programming language, they invariably run afoul of the best practices that ensure the efficient processing and execution of the code. Because T-SQL is at its best when manipulating sets of data, try to keep that fact foremost in your thoughts during the process of developing T-SQL code.
With the release of SQL Server 2005, Microsoft muddied the waters a bit with the ability to write calls to the database in a programming language like C# or VB.NET, rather than in pure SQL. SQL Server 2008 also supports this very flexible capability, but use caution! Although this is a very exciting innovation in data access, the truth of the matter is that almost all calls to the database engine must still be manipulated so that they appear to be T-SQL based.
Performing multiple recursive row operations or complex mathematical computations is quite possible with T-SQL, but so is writing a .NET application with Notepad. When I was growing up my father used to make a point of telling me that “Just because you can do something doesn’t mean you should.” The point here is that oftentimes SQL programmers will resort to creating custom objects in their code that are inefficient as far as memory and CPU consumption are concerned. They do this because it is the easiest and quickest way to finish the code. I agree that there are times when a quick solution is the best, but future performance must always be taken into account.
One of the systems I am currently working on is a perfect example of this problem. The database started out very small, with a small development team and a small number of customers using the database. It worked great. However, the database didn’t stay small, and as more and more customers started using the system, the number of transactions and code executions increased exponentially. It wasn’t long before inefficient code began to consume all the available CPU resources. This is the trap of writing expedient code instead of efficient code. Another of my father’s favorite sayings is “Why is there never enough time to do the job right, but plenty of time to do it twice?” This book tries to show you the best way to write T-SQL so that you can avoid writing code that will bring your server to its knees, begging for mercy. Don’t give in to the temptation to write sloppy code just because it is a “one time deal.” I have seen far too many times when that one-off ad-hoc query became a central piece of an application’s business logic.
What’s New in SQL Server 2008
When SQL Server 2005 was released, it had been five years since the previous release and the changes to the product since the release of SQL Server 2000 were myriad and significant. Several books and hundreds of websites were published that were devoted to the topic of “What’s New in SQL Server 2005.” With the release of SQL Server 2008, however, there is much less buzz and not such a dramatic change to the platform. However, the changes in the 2008 release are still very exciting and introduce many changes that T-SQL and application developers have been clamoring for. Since these changes are sprinkled throughout the capabilities of SQL Server, I won’t spend a great deal of time describing all the changes here. Instead, throughout the book I will identify those changes that are applicable to the subject being described. In this introductory chapter I want to quickly mention two of the significant changes to SQL that will invariably have an impact on the SQL programmer: the incorporation of the .NET Framework with SQL Server and the introduction of Microsoft Language Integrated Query (LINQ).
Kiss T-SQL Goodbye?
I have been hearing for years that T-SQL and its ANSI counterpart, SQL, were antiquated languages and would soon be phased out. However, every database vendor, both small and large, has devoted millions of dollars to improving their version of this versatile language. Why would they do that if it were a dead language? The simple fact of the matter is that databases are built and optimized for the set-based operations that the SQL language offers. Is there a better way to access and manipulate data? Probably so, but with every major industry storing their data in relational databases, the reign of SQL is far from over.
I worked for a great guy at a Microsoft partner company who was contracted by Microsoft to develop and deliver a number of SQL Server and Visual Studio evangelism presentations. Having a background in radio sales and marketing, he came up with a cool tagline about SQL Server and the .NET Framework that said “SQL Server and .NET — Kiss T-SQL Goodbye.” He was quickly dissuaded by his team when presented with the facts. However, Todd wasn’t completely wrong. What his catchy tagline could have said and been accurate was “SQL Server and .NET — Kiss Inefficient, CPU-Hogging T-SQL Code Goodbye.”
Two significant improvements in data access over the last two releases of SQL Server have offered fuel for the “SQL is dead” fire. As I mentioned briefly before, these are the incorporation of the .NET Framework and the development of LINQ. LINQ is Microsoft’s latest application data-access technology. It enables Visual Basic and C# applications to use set-oriented queries that are developed in C# or VB, rather than requiring that the queries be written in T-SQL. Building in the .NET Framework to the SQL Server engine enables developers to create SQL Server programming objects such as stored procedures, functions, and aggregates using any .NET language and compiling them into Common Language Runtime (CLR) assemblies that can be referenced directly by the database engine.
So with the introduction of LINQ in SQL Server 2008 and CLR integration in SQL Server 2005, is T-SQL on its death bed? No, not really. Reports of T-SQL’s demise are premature and highly exaggerated. The ability to create database programming objects in managed code instead of SQL does not mean that T-SQL is in danger of becoming extinct. Likewise, the ability to create set-oriented queries in C# and VB does not sound the death knell for T-SQL. SQL Server’s native language is still T-SQL. LINQ will help in the rapid development of database applications, but it remains to be seen if this technology will match the performance of native T-SQL code run from the server. This is because LINQ data access still must be translated from the application layer to the database layer, but T-SQL does not. It’s a fantastic and flexible access layer for smaller database applications, but for large, enterprise-class applications, LINQ, like embedded SQL code in applications before it, falls short of pure T-SQL in terms of performance.
What was true then is true now. T-SQL will continue to be the core language for applications that need to add, extract, and manipulate data stored on SQL Server. Until the data engine is completely re-engineered (and that day will inevitably come), T-SQL will be at the heart of SQL Server.
Database Management Systems
A database management system (DBMS) is a set of programs designed to store and maintain data. The role of the DBMS is to manage the data so that the consistency and integrity of the data is maintained above all else. Quite a few types and implementations of database management systems exist:
Hierarchical database management systems (HDBMS) — Hierarchical databases have been around for a long time and are perhaps the oldest of all databases. They were (and in some cases still are) used to manage hierarchical data. They have several limitations, such as being able to manage only single trees of hierarchical data and the inability to efficiently prevent erroneous or duplicate data. HDBMS implementations are getting increasingly rare and are constrained to specialized, and typically non-commercial, applications.Network database management system (NDBMS) — The NDBMS has been largely abandoned. In the past, large organizational database systems were implemented as network or hierarchical systems. The network systems did not suffer from the data inconsistencies of the hierarchical model, but they did suffer from a very complex and rigid structure that made changes to the database or its hosted applications very difficult.Relational database management system (RDBMS) — An RDBMS is a software application used to store data in multiple related tables using SQL as the tool for creating, managing, and modifying both the data and the data structures. An RDBMS maintains data by storing it in tables that represent single entities, such as “Customer” and “Sale” and storing information about the relationship of these tables to each other in yet more tables managed by the system which define the relationship between the Sale table and the Customer table. The concept of a relational database was first described by E. F. Codd, an IBM scientist who defined the relational model in 1970. Relational databases are optimized for recording transactions and the resultant transactional data. Most commercial software applications use an RDBMS as their data store. Because SQL was designed specifically for use with an RDBMS, I will spend a little extra time covering the basic structures of an RDBMS later in this chapter.Object-oriented database management system (ODBMS) — The ODBMS emerged a few years ago as a system where data was stored as objects in a database. ODBMS supports multiple classes of objects and inheritance of classes along with other aspects of object orientation. Currently, no international standard exists that specifies exactly what an ODBMS is and what it isn’t.Because ODBMS applications store objects instead of related entities, they make the system very efficient when dealing with complex data objects and object-oriented programming (OOP) languages such as the .NET languages from Microsoft as well as C and Java. When ODBMS solutions were first released, they were quickly touted as the ultimate database system and predicted to make all other database systems obsolete. However, they never achieved the wide acceptance that was predicted. They do have a very valid position in the database market, but it is a niche market held mostly within the Computer-Aided Design (CAD) and telecommunications industries.
SQL Server as a Relational Database Management System
This section introduces you to the concepts behind relational databases and how they are implemented from a Microsoft viewpoint. This will, by necessity, skirt the edges of database object creation, which is covered in great detail in Chapter 13, so for the purpose of this discussion I will avoid the exact mechanics and focus on the final results.
As I mentioned earlier, a relational database stores all its data inside tables. Ideally, each table will represent a single entity or object. You would not want to create one table that contained data about both dogs and cars. That isn’t to say you couldn’t do this, but it wouldn’t be very efficient or easy to maintain if you did.
Tables
Tables are divided up into rows and columns. Each row must be able to stand on its own, without a dependency to other rows in the table. The row must represent a single, complete instance of the entity the table was created to represent. Each column in the row contains specific attributes that help define the instance. This may sound a bit complex, but it is actually very simple. To help illustrate, consider a real-world entity, such as an employee. If you want to store data about an employee, you would need to create a table that has the properties you need to record data about your employee. For simplicity’s sake, call your table Employee.
When you create your employee table, you also need to decide which attributes of the employee you want to store. For the purposes of this example, suppose that you have decided to store the employee’s last name, first name, Social Security number, department, extension, and hire date. The resulting table would look something like that shown in Figure 1-1.
Figure 1-1
The data in the table would look something like that shown in Figure 1-2.
Figure 1-2
Primary Keys
To manage the data in your table efficiently, you need to be able to uniquely identify each individual row in the table. It is much more difficult to retrieve, update, or delete a single row if there is not a single attribute that identifies each row individually. In many cases, this identifier is not a descriptive attribute of the entity. For example, the logical choice to uniquely identify your employee is the Social Security number attribute. However, there are a couple of reasons why you would not want to use the Social Security number as the primary mechanism for identifying each instance of an employee, both boiling down to two different areas: security and efficiency.
When it comes to security, what you want to avoid is the necessity of securing the employee’s Social Security number in multiple tables. Because you will most likely be using the key column in multiple tables to form your relationships (more on that in a moment), it makes sense to substitute a non-descriptive key. In this way you avoid the issue of duplicating private or sensitive data in multiple locations to provide the mechanism to form relationships between tables.
As far as efficiency is concerned, you can often substitute a non-data key that has a more efficient or smaller data type associated with it. For example, in your design you might have created the Social Security number with either a character data type or an integer. If you have fewer than 32,767 employees, you can use a double-byte integer instead of a 4-byte integer or 10-byte character type; besides, integers process faster than characters.
So, instead of using the Social Security number, you will assign a non-descriptive key to each row. The key value used to uniquely identify individual rows in a table is called a primary key. (You will still want to ensure that every Social Security number in your table is unique and not null, but you will use a different method to guarantee this behavior without making it a primary key.)
A non-descriptive key doesn’t represent anything else with the exception of being a value that uniquely identifies each row or individual instance of the entity in a table. This will simplify the joining of this table to other tables and provide the basis for a “relation.” In this example you will simply alter the table by adding an EmployeeKey column that will uniquely identify every row in the table, as shown in Figure 1-3.
Figure 1-3
With the EmployeeKey column, you have an efficient, easy-to-manage primary key.
Each table can have only one primary key, which means that this key column is the primary method for uniquely identifying individual rows. It doesn’t have to be the only mechanism for uniquely identifying individual rows; it is just the “primary” mechanism for doing so. Primary keys can never be null, and they must be unique. Primary keys can also be combinations of columns (though I’ll explain later why I am a firm believer that primary keys should typically be single-column keys). If you have a table where two columns in combination are unique, while either single column is not, you can combine the two columns as a single primary key, as illustrated in Figure 1-4.
Figure 1-4
In this example, the LibraryBook table is used to maintain a record of every book in the library. Because multiple copies of each book can exist, the ISBN column is not useful for uniquely identifying each book. To enable the identification of each individual book, the table designer decided to combine the ISBN column with the copy number of each book. Personally, I avoid the practice of using multiple column keys. I prefer to create a separate column that can uniquely identify the row. This makes it much easier to write join queries (covered in detail in Chapter 8). The resulting code is cleaner and the queries are generally more efficient. For the library book example, a more efficient mechanism might be to assign each book its own number. The resulting table would look like that shown in Figure 1-5.
Figure 1-5
Table Columns
As previously described, a table is a set of rows and columns used to represent an entity. Each row represents an instance of the entity. Each column in the row will contain at most one value that represents an attribute, or property, of the entity. For example, consider the employee table; each row represents a single instance of the employee entity. Each employee can have one and only one first name, last name, SSN, extension, or hire date, according to your design specifications. In addition to deciding which attributes you want to maintain, you must also decide how to store those attributes. When you define columns for your tables, you must, at a minimum, define three things:
The name of the columnThe data type of the columnWhether the column can support nullColumn Names
Keep the names simple and intuitive (such as LastName or EmployeeID) instead of more cumbersome names (such as EmployeeLastName and EmployeeIdentificationNumber). For more information, see Chapter 8.
Data Types
The general rule on data types is to use the smallest one you can. This conserves memory usage and disk space. Also keep in mind that SQL Server processes numbers much more efficiently than characters, so use numbers whenever practical. I have heard the argument that numbers should be used only if you plan on performing mathematical operations on the columns that contain them, but that just doesn’t wash. Numbers are preferred over string data for sorting and comparison as well as mathematical computations. The exception to this rule is if the string of numbers you want to use starts with a zero. Take the Social Security number, for example. Other than the unfortunate fact that some Social Security numbers begin with a zero, the Social Security number would be a perfect candidate for using an integer instead of a character string. However, if you tried to store the integer 012345678, you would end up with 12345678. These two values may be numeric equivalents, but the government doesn’t see it that way. They are strings of numerical characters and therefore must be stored as characters rather than as numbers.
When designing tables and choosing a data type for each column, try to be conservative and use the smallest, most efficient type possible. But at the same time, carefully consider the exception, however rare, and make sure that the chosen type will always meet these requirements.
The data types available for columns in SQL Server 2005 and 2008 are specified in the following table. Those that are unique to SQL Server 2008 are prefixed with an asterisk (*).
Data TypeStorageDescriptionIntegersNote: Signed integers can be both positive and negative, whereas unsigned integers have no inherent signed valuebigint8 bytesAn 8-byte signed integer. Valid values are −9223372036854775808 through +9223372036854775807.int4 bytesA 4-byte signed integer. Valid values are −2,147,483,648 through +2,147,483,647.smallint2 bytesA double-byte signed integer. Valid values are −32,768 through +32,767.tinyint1 byteA single-byte unsigned integer. Valid values are from 0 through 255.bit1 bitInteger data with either a 1 or 0 value.Exact Numericsdecimal5–17 bytesA predefined, fixed, signed decimal number ranging from −100000000000000000000000000000000000001 (−1038+1) to 99999999999999999999999999999999999999 (+1038−1). A decimal is declared with a precision and scale value that determines how many decimal places to the left and right are supported. This is expressed as decimal[(precision,[scale])]. The precision setting determines how many total digits to the left and right of the decimal point are supported. The scale setting determines how many digits to the right of the decimal point are supported. For example, to support the number 3.141592653589793, the decimal data type would have to be specified as decimal(16,15). If the data type were specified as decimal(3,2), only 3.14 would be stored. The scale defaults to zero and must be between 0 and the precision. The precision defaults to 18 and can be a maximum of 38.numeric5–17 bytesThe numeric data type is identical to the decimal data type, so use decimal instead, for consistency. The numeric data type is much less descriptive because most people think of integers as being numeric.money8 bytesThe money data type can be used to store values from −922,337,203,685,477.5808 to +922,337,203,685,477.5807 of a monetary unit, such as a dollar, euro, pound, and so on. The advantage of the money data type over a decimal data type is that developers can take advantage of automatic currency formatting for specific locales. Notice that the money data type supports figures to the fourth decimal place. Accountants like that. A few million of those ten thousandths of a penny add up after a while!smallmoney4 bytesBill Gates needs the money data type to track his portfolio, but most of us can get by with the smallmoney data type. It consumes 4 bytes of storage and can be used to store values of −214,748.3648 to +214,748.3647 of a monetary unit.Approximate Numericsfloat4 or 8 bytesThe float data type is an approximate value (SQL Server performs rounding) that supports real numbers in the range of −1.79E + 308 to −2.23E − 308, 0 and 2.23E − 308 to 1.79E + 308. float can be used as a 4-byte or 8-byte data type, depending on an optional mantissa value (the number of bits used to store the mantissa of the float). float(24) or any value between 1 and 24 will cause the float to be defined as a 4-byte value that can store real numbers in the range of −3.40E + 38 to −1.18E − 38, 0 and 1.18E − 38 to 3.40E + 38. Any number between 25 and 53 will cause the float to be defined as an 8-bit float (aka, a double precision) in the default manner of float(53).real4 bytesThe real data type is a synonym for a 4-byte float.Date and TimeData Typesdatetime8 bytesThe datetime data type is used to store date and time from January 1, 1753 through December 31, 9999. The accuracy of the datetime data type is 3.33 milliseconds.*datetime28 bytesThe datetime2 data type is used to store date and time from January 1, 0001 through December 31, 9999. The accuracy of the datetime2 data type is variable but defaults to 100 nanoseconds.smalldatetime4 bytesThe smalldatetime data type stores date and time from January 1, 1900 through June 6, 2079, with an accuracy of 1 minute.*date3 bytesThe date data type stores dates only from January 1, 0001 through December 31, 9999, with an accuracy of 1 day.*time5 bytesThe time data type stores time-only data, with a variable precision of up to 100 nanoseconds*datetimeoffset10 bytesThe datetimeoffset data type is used to store date and time from January 1, 0001 through December 31, 9999. The accuracy of the datetimeoffset data type varies based on the type of server hardware SQL Server is installed on, but defaults to 100 nanoseconds if supported. When defined, the datetimeoffset data type expects a date and time string to be specified along with a time zone offset. Possible time zone offsets are between −14.00 and +14.00 hours. For example, to define a variable that is time-zone aware for Pacific Standard Time, the following code would be used:DECLARE @PacificTime AS datetimeoffset(8)Character Data Typeschar1 byte per character. Maximum 8000 characters.The char data type is a fixed-length data type used to store character data. The number of possible characters is between 1 and 8000. The possible combinations of characters in a char data type are 256. The characters that are represented depend on what language, or collation, is defined. English, for example, is actually defined with a Latin collation. The Latin collation provides support for all English and western European characters.varchar1 byte per character. Up to 2GB characters.The varchar data type is identical to the char data type, but with a variable length. If a column is defined as char(8), it will consume 8 bytes of storage even if only three characters are placed in it. A varchar column consumes only the space it needs. Typically, char data types are more efficient when it comes to processing and varchar data types are more efficient for storage. The rule of thumb is to use char if the data will always be close to the defined length, but use varchar if it will vary widely. For example, a city name would be stored with varchar(167) if you wanted to allow for the longest city name in the world, which is Krung thep mahanakhon bovorn ratanakosin mahintharayutthaya mahadilok pop noparatratchathani burirom udomratchanivetmahasathan amornpiman avatarnsathit sakkathattiyavisnukarmprasit (the poetic name of Bangkok, Thailand). Use char for data that is always the same. For example, you could use char(12) to store a domestic phone number in the United States: (123)456-7890. The 8000-byte limitation can be exceeded by specifying the (MAX) option (varchar(MAX)), which allows for the storage of 2,147,483,647 characters at the cost of up to 2GB storage space.text1 byte per character. Maximum 2,147,483,648 characters (2GB).The text data type is similar to the varchar data type in that it is a variable-length character data type. The significant difference is the maximum length of about 2 billion characters (including spaces) and where the data is physically stored. With a varchar data type on a table column, the data is stored physically in the row with the rest of the data. With a text data type, the data is stored separately from the actual row and a pointer is stored in the row so that SQL Server can find the text. The text data type is functionally equivalent to the varchar(MAX) data type.nchar2 bytes per character. Maximum 4000 characters (8000 bytes).The nchar data type is a fixed-length type identical to the char data type, with the exception of the number of characters supported. char data is represented by a single byte and thus only 256 different characters can be supported. nchar is a double-byte data type and can support 65,536 different characters. The cost of the extra character support is the double-byte length, so the maximum nchar length is 4000 characters or 8000 bytes.nvarchar2 bytes per character. Up to 2GB.The nvarchar data type is a variable-length type identical to the varchar data type, with the exception of the amount of characters supported. varchar data is represented by a single byte and only 256 different characters can be supported. nvarchar is a double-byte data type and can support 65,536 different characters. The cost of the extra character support is the double-byte length, so the maximum nvarchar length is 4000 characters or 8000 bytes. This limit can be exceeded by using the (MAX) option, which allows for the storage of 1,073,741,823 characters in 2GB.ntext2 bytes per character. Maximum 1,073,741,823 characters.The ntext data type is identical to the text data type, with the exception of the number of characters supported. text data is represented by a single byte and only 256 different characters can be supported. ntext is a double-byte data type and can support 65,536 different characters. The cost of the extra character support is the double-byte length, so the maximum ntext length is 1,073,741,823 characters or 2GB. The ntext data type is functionally equivalent to the nvarchar(MAX) data type.Binary Data Typesbinary1–8000 bytesFixed-length binary data. Length is fixed when created between 1 and 8000 bytes. For example, binary(5000) specifies the reserving of 5000 bytes of storage to accommodate up to 5000 bytes of binary data.varbinaryUp to 2,147,483,647 bytesVariable-length binary data type identical to the binary data type, with the exception of consuming only the amount of storage that is necessary to hold the data. Using the (MAX) option allows for the storage of up to 2GB of binary data. However, only 1 through 8000 or MAX can be specified as storage options.imageUp to 2,147,483,647 bytesThe image data type is similar to the varbinary data type in that it is a variable-length binary data type. The significant difference is the maximum length of about 2GB and where the data is physically stored. With a varbinary data type on a table column, the data is stored physically in the row with the rest of the data. With an image data type, however, the data is stored separately from the actual row and a pointer is stored in the row so that SQL Server can find the data. Typically, image data types are used to store actual images, binary documents, or binary objects. The image data type is functionally identical to varbinary(MAX).Other Data Typestimestamp8 bytesThe timestamp data type has nothing to do with time. It is more accurately described as a data type that maintains row version data. In light of this fact, a system alias of rowversion is available for this data type and is generally preferred to avoid confusion. What timestamp actually provides is a database unique identifier to identify a version of a row. Every time a row that contains a timestamp data type is modified, the value of the timestamp changes.uniqueidentifier32 bytesA data type used to store a globally unique identifier (GUID).*hierarchyidUp to 892 bytesThe hierarchyid data type is a variable length data type that is used to represent position in a hierarchy.sql_variantUp to 8016 bytessql_variant is used when the exact data type is unknown. It can be used to hold any data type with the exception of text, ntext, image, and timestamp.xmlUp to 2GBThe xml data type is used to store well-formed XML. The XML stored can be specified to be well-formed fragments or complete documents and can be enforced with an XML schema bound to the variable, parameter, or column containing the XML data.SQL Server supports additional data types, listed in the following table, that can be used in queries and programming objects, but they are not used to define columns.
Data TypeDescriptioncursorThe cursor data type is used to point to an instance of a cursor.tableThe table data type is used to store an in-memory rowset for processing. It was developed primarily for use with the table-valued functions that were introduced in SQL Server 2000.Nullability
All rows from the same table have the same set of columns. However, not all columns will necessarily have values in them. For example, a new employee is hired, but he has not been assigned an extension yet. In this case, the extension column may not have any data in it. Instead, it may contain null, which means the value for that column was not initialized. Note that a null value for a string column is different from an empty string. An empty string is defined; a null is not. You should always consider a null as an unknown value. When you design your tables, you need to decide whether to allow a null condition to exist in your columns. Nulls can be allowed or disallowed on a column-by-column basis, so your employee table design could look like that shown in Figure 1-6.
Figure 1-6
Relationships
Relational databases are all about relations. To manage these relations, you use common keys. For example, your employees sell products to customers. This process involves multiple entities:
The employeeThe productThe customerThe saleTo identify which employee sold which product to which customer, you need some way to link together all the entities. Typically, these links are managed through the use of keys — primary keys in the parent table and foreign keys in the child table.
As a practical example, you can revisit the employee example. When your employee sells a product, his or her identifying information is added to the Sale table to record who the responsible employee was, as illustrated in Figure 1-7. In this case, the Employee table is the parent table and the Sale table is the child table.
Figure 1-7
Because the same employee could sell products to many customers, the relationship between the Employee table and the Sale table is called a one-to-many relationship. The fact that the employee is the unique participant in the relationship makes it the parent table. Relationships are very often parent-child relationships, which means that the record in the parent table must exist before the child record can be added. In the example, because every employee is not required to make a sale, the relationship is more accurately described as a one-to-zero-or-more relationship. In Figure 1-7 this relationship is represented by a key and infinity symbol, which doesn’t adequately model the true relationship because you don’t know if the EmployeeKey field is nullable. In Figure 1-8, the more traditional and informative “crows feet” symbol is used. The relationship symbol in this figure represents an exactly one (the double vertical lines) to zero (the ring) or more (the crows feet) relationship. Figure 1-9 shows the two tables with an exactly one to one or more relationship symbol. The PK abbreviation stands for primary key, while the FK stands for foreign key. Because a table can have multiple foreign keys, they are numbered sequentially starting at 1.
Figure 1-8
Figure 1-9
Relationships can be defined as follows:
One-to-zero or moreOne-to-one or moreOne-to-exactly-oneMany-to-manyThe many-to-many relationship requires three tables because a many-to-many constraint would be unenforceable. An example of a many-to-many relationship is illustrated in Figure 1-10. The necessity for this relationship is created by the relationships between your entities: In a single sale many products can be sold, but one product can be in many sales. This creates the many-to-many relationship between the Sale table and the Product table. To uniquely identify every product and sale combination, you need to create what is called a linking table. A linking table is simply another table that contains the combination of primary keys from the two tables, as illustrated in Figure 1-10
