“Given the authors’ reputations, I expected to be impressed. I was blown away! . . . Most SQL books sit on my shelf. This one will live on my desk.” –Roger Carlson, Microsoft Access MVP (2006-2015) “Rather than stumble around reinventing wheels or catching glimpses of the proper approaches, do yourself a favor: Buy this book.” —Dave Stokes, MySQL Community Manager, Oracle Corporation Effective SQL brings together practical solutions and insights so you can solve complex problems with SQL and design databases that simplify data management in the future. It’s the only modern book that brings together advanced best practices and realistic example code for all of these versions of SQL: IBM DB2, Microsoft Access, Microsoft SQL Server, MySQL, Oracle Database, and PostgreSQL. Drawing on their immense experience as world-class database consultants and instructors, the authors identify 61 proven approaches to writing better SQL. Wherever SQL versions vary, the authors illuminate the key nuances, so you can get the most out of whatever version you prefer. This full-color guide provides clear, practical explanations; expert tips; and plenty of usable code. Going far beyond mere syntax, it addresses issues ranging from optimizing database designs to managing hierarchies and metadata. If you already know SQL’s basics, this guide will help you become a world-class SQL problem-solver. Craft better logical data models, and fix flawed models Implement indexes that improve query performance Handle external data from sources you don’t control Extract and aggregate the information you need, as efficiently as possible Write more flexible subqueries Analyze and retrieve metadata using your database platform of choice Use Cartesian Products and Tally Tables to solve problems you can’t address with conventional JOINs Model hierarchical data: managing SQL’s tradeoffs and shortcomings

Table of Contents:
Foreword xiii Acknowledgments xv About the Authors xvii About the Technical Editors xix   Introduction 1 A Brief History of SQL 1 Database Systems We Considered 5 Sample Databases 6 Where to Find the Samples on GitHub 7 Summary of the Chapters 8   Chapter 1: Data Model Design 11 Item 1: Verify That All Tables Have a Primary Key 11 Item 2: Eliminate Redundant Storage of Data Items 15 Item 3: Get Rid of Repeating Groups 19 Item 4: Store Only One Property per Column 21 Item 5: Understand Why Storing Calculated Data Is Usually a Bad Idea 25 Item 6: Define Foreign Keys to Protect Referential Integrity 30 Item 7: Be Sure Your Table Relationships Make Sense 33 Item 8: When 3NF Is Not Enough, Normalize More 37 Item 9: Use Denormalization for Information Warehouses 43   Chapter 2: Programmability and Index Design 47 Item 10: Factor in Nulls When Creating Indexes 47 Item 11: Carefully Consider Creation of Indexes to Minimize Index and Data Scanning 52 Item 12: Use Indexes for More than Just Filtering 56 Item 13: Don’t Go Overboard with Triggers 61 Item 14: Consider Using a Filtered Index to Include or Exclude a Subset of Data 65 Item 15: Use Declarative Constraints Instead of Programming Checks 68 Item 16: Know Which SQL Dialect Your Product Uses and Write Accordingly 70 Item 17: Know When to Use Calculated Results in Indexes 74   Chapter 3: When You Can’t Change the Design 79 Item 18: Use Views to Simplify What Cannot Be Changed 79 Item 19: Use ETL to Turn Nonrelational Data into Information 85 Item 20: Create Summary Tables and Maintain Them 90 Item 21: Use UNION Statements to “Unpivot” Non-normalized Data 94   Chapter 4: Filtering and Finding Data 101 Item 22: Understand Relational Algebra and How It Is Implemented in SQL 101 Item 23: Find Non-matches or Missing Records 108 Item 24: Know When to Use CASE to Solve a Problem 110 Item 25: Know Techniques to Solve Multiple-Criteria Problems 115 Item 26: Divide Your Data If You Need a Perfect Match 120 Item 27: Know How to Correctly Filter a Range of Dates on a Column Containing Both Date and Time 124 Item 28: Write Sargable Queries to Ensure That the Engine Will Use Indexes 127 Item 29: Correctly Filter the “Right” Side of a “Left” Join 132   Chapter 5: Aggregation 135 Item 30: Understand How GROUP BY Works 135 Item 31: Keep the GROUP BY Clause Small 142 Item 32: Leverage GROUP BY/HAVING to Solve Complex Problems 145 Item 33: Find Maximum or Minimum Values Without Using GROUP BY 150 Item 34: Avoid Getting an Erroneous COUNT() When Using OUTER JOIN 156 Item 35: Include Zero-Value Rows When Testing for HAVING COUNT(x) < Some Number 159 Item 36: Use DISTINCT to Get Distinct Counts 163 Item 37: Know How to Use Window Functions 166 Item 38: Create Row Numbers and Rank a Row over Other Rows 169 Item 39: Create a Moving Aggregate 172   Chapter 6: Subqueries 179 Item 40: Know Where You Can Use Subqueries 179 Item 41: Know the Difference between Correlated and Non-correlated Subqueries 184 Item 42: If Possible, Use Common Table Expressions Instead of Subqueries 190 Item 43: Create More Efficient Queries Using Joins Rather than Subqueries 197   Chapter 7: Getting and Analyzing Metadata 201 Item 44: Learn to Use Your System’s Query Analyzer 201 Item 45: Learn to Get Metadata about Your Database 212 Item 46: Understand How the Execution Plan Works 217   Chapter 8: Cartesian Products 227 Item 47: Produce Combinations of Rows between Two Tables and Flag Rows in the Second That Indirectly Relate to the First 227 Item 48: Understand How to Rank Rows by Equal Quantiles 231 Item 49: Know How to Pair Rows in a Table with All Other Rows 235 Item 50: Understand How to List Categories and the Count of First, Second, or Third Preferences 240   Chapter 9: Tally Tables 247 Item 51: Use a Tally Table to Generate Null Rows Based on a Parameter 247 Item 52: Use a Tally Table and Window Functions for Sequencing 252 Item 53: Generate Multiple Rows Based on Range Values in a Tally Table 257 Item 54: Convert a Value in One Table Based on a Range of Values in a Tally Table 261 Item 55: Use a Date Table to Simplify Date Calculation 268 Item 56: Create an Appointment Calendar Table with All Dates Enumerated in a Range 275 Item 57: Pivot Data Using a Tally Table 278   Chapter 10: Modeling Hierarchical Data 285 Item 58: Use an Adjacency List Model as the Starting Point 286 Item 59: Use Nested Sets for Fast Querying Performance with Infrequent Updates 288 Item 60: Use a Materialized Path for Simple Setup and Limited Searching 291 Item 61: Use Ancestry Traversal Closure for Complex Searching 294   Appendix: Date and Time Types, Operations, and Functions 299 IBM DB2 299 Microsoft Access 303 Microsoft SQL Server 305 MySQL 308 Oracle 313 PostgreSQL 315   Index 317