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SQL Query Design Patterns and Best Practices

You're reading from   SQL Query Design Patterns and Best Practices A practical guide to writing readable and maintainable SQL queries using its design patterns

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Product type Paperback
Published in Mar 2023
Publisher Packt
ISBN-13 9781837633289
Length 270 pages
Edition 1st Edition
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Authors (6):
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Chi Zhang Chi Zhang
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Chi Zhang
Steven Hughes Steven Hughes
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Steven Hughes
Shabbir Mala Shabbir Mala
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Shabbir Mala
Dennis Neer Dennis Neer
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Dennis Neer
Leslie Andrews Leslie Andrews
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Leslie Andrews
Ram Babu Singh Ram Babu Singh
Author Profile Icon Ram Babu Singh
Ram Babu Singh
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Table of Contents (21) Chapters Close

Preface 1. Part 1: Refining Your Queries to Get the Results You Need
2. Chapter 1: Reducing Rows and Columns in Your Result Sets FREE CHAPTER 3. Chapter 2: Efficiently Aggregating Data 4. Chapter 3: Formatting Your Results for Easier Consumption 5. Chapter 4: Manipulating Data Results Using Conditional SQL 6. Part 2: Solving Complex Business and Data Problems in Your Queries
7. Chapter 5: Using Common Table Expressions 8. Chapter 6: Analyze Your Data Using Window Functions 9. Chapter 7: Reshaping Data with Advanced Techniques 10. Chapter 8: Impact of SQL Server Security on Query Results 11. Part 3: Optimizing Your Queries to Improve Performance
12. Chapter 9: Understanding Query Plans 13. Chapter 10: Understanding the Impact of Indexes on Query Design 14. Part 4: Working with Your Data on the Modern Data Platform
15. Chapter 11: Handling JSON Data in SQL Server 16. Chapter 12: Integrating File Data and Data Lake Content with SQL 17. Chapter 13: Organizing and Sharing Your Queries with Jupyter Notebooks 18. Index 19. Other Books You May Enjoy Appendix: Preparing Your Environment

Summary

In this chapter, we learned how to use the PIVOT and UNPIVOT operators and how we can use them in our advanced query techniques by transforming rows into columns or vice versa. We looked at a few examples and also learned how to dynamically construct column names that are used in pivoting operations. Both of these operators are very powerful and are a very good and clean replacement for the lengthy CASE statement we studied in Chapter 4.

The PIVOT option is used a lot for reporting purposes and analyzing data in different formats and UNPIVOT is more for denormalizing datasets and storing them in SQL tables.

Next, we looked at the new way of storing hierarchical data, using the hierarchyid data type. We walked through a very typical use case of storing organization hierarchy data with examples.

In the next chapter, we will move our focus onto the security aspects of SQL queries and the things we need to take care of while querying data from a database, along with how...

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