SQL Query Design Patterns and Best Practices: A practical guide to writing readable and maintainable SQL queries using its design patterns

Cover Page....2

Table of Contents....3

Preface....5

Part 1: Refining Your Queries to Get the Results You Need....15

Chapter 1: Reducing Rows and Columns in Your Result Sets....16

Technical requirements....16

Identifying data to remove from the dataset....17

Understanding the value of creating views versus removing data....23

Exploring the impact of row and column reductions on aggregations....26

Summary....31

Chapter 2: Efficiently Aggregating Data....32

Technical requirements....32

Identifying data to be aggregated....33

Determining when data should be aggregated....35

Improving performance when aggregating data....44

Summary....47

Chapter 3: Formatting Your Results for Easier Consumption....49

Technical requirements....50

Formatting dates and numbers with functions....57

Alias columns with meaningful names....64

Summary....65

Chapter 4: Manipulating Data Results Using Conditional SQL....67

Technical requirements....67

Using the CASE statement....68

Using the COALESCE() expression....80

Using ISNULL() function....84

Summary....87

Part 2: Solving Complex Business and Data Problems in Your Queries....89

Chapter 5: Using Common Table Expressions....90

Technical requirements....90

Creating CTEs....91

Creating a recursive CTE....97

Summary....102

Chapter 6: Analyze Your Data Using Window Functions....103

Technical requirements....103

Understanding window functions....104

Scenarios and business problems....115

Chapter 7: Reshaping Data with Advanced Techniques....128

Technical requirements....128

Working with the PIVOT operator....129

Working with the UNPIVOT operator....136

Understanding hierarchical data....139

Summary....143

Chapter 8: Impact of SQL Server Security on Query Results....145

Technical requirements....145

Why is data missing from my result set?....146

Understanding SQL Server security....148

Validating security settings....149

Summary....153

Part 3: Optimizing Your Queries to Improve Performance....154

Chapter 9: Understanding Query Plans....155

Technical requirements....155

Understanding query optimization techniques....156

Understanding the Query Optimizer....156

Understanding and exploring the Query Execution Plan....157

Summary....180

Chapter 10: Understanding the Impact of Indexes on Query Design....182

Technical requirements....182

Understanding index and index types....183

Using CREATE to create an index....183

Exploring the types of indexes....190

The impact of indexes on query design....197

Understanding index maintenance....201

Summary....205

Further reading....205

Part 4: Working with Your Data on the Modern Data Platform....206

Chapter 11: Handling JSON Data in SQL Server....207

Technical requirements....207

Introducing JSON functionality built into SQL Server....208

JSON path in SQL Server....212

Formatting results as JSON in SQL Server....213

Working with JSON data in SQL queries....224

Building tabular results from JSON data in SQL Server....231

Summary....234

Chapter 12: Integrating File Data and Data Lake Content with SQL....235

Technical requirements....235

Understanding the OPENROWSET (BULK..) function....236

Required security and storage permissions....244

Understanding external tables....247

Summary....253

Chapter 13: Organizing and Sharing Your Queries with Jupyter Notebooks....255

Technical requirements....255

Creating Jupyter notebooks in Azure Data Studio....256

Adding queries in your Jupyter notebooks....264

Documenting your code with markdown in your notebooks....275

Managing and sharing your queries with Jupyter notebooks....280

Summary....284

Index....285

Why subscribe?....301

Other Books You May Enjoy....303

Packt is searching for authors like you....307

Share Your Thoughts....307

Download a free PDF copy of this book....308

Appendix: Preparing Your Environment....310

SQL has been the de facto standard when interacting with databases for decades and shows no signs of going away. Through the years, report developers or data wranglers have had to learn SQL on the fly to meet the business needs, so if you are someone who needs to write queries, SQL Query Design and Pattern Best Practices is for you.

This book will guide you through making efficient SQL queries by reducing set sizes for effective results. You'll learn how to format your results to make them easier to consume at their destination. From there, the book will take you through solving complex business problems using more advanced techniques, such as common table expressions and window functions, and advance to uncovering issues resulting from security in the underlying dataset. Armed with this knowledge, you'll have a foundation for building queries and be ready to shift focus to using tools, such as query plans and indexes, to optimize those queries. The book will go over the modern data estate, which includes data lakes and JSON data, and wrap up with a brief on how to use Jupyter notebooks in your SQL journey.

By the end of this SQL book, you'll be able to make efficient SQL queries that will improve your report writing and the overall SQL experience.

What You Will Learn:

• Build efficient queries by reducing the data being returned
• Manipulate your data and format it for easier consumption
• Form common table expressions and window functions to solve complex business issues
• Understand the impact of SQL security on your results
• Understand and use query plans to optimize your queries
• Understand the impact of indexes on your query performance and design
• Work with data lake data and JSON in SQL queries
• Organize your queries using Jupyter notebooks

Who this book is for:

This book is for SQL developers, data analysts, report writers, data scientists, and other data gatherers looking to expand their skills for complex querying as well as for building more efficient and performant queries.

For those new to SQL, this book can help you accelerate your learning and keep you from making common mistakes.