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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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Toc

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

Understanding window functions

A window function operates over a set of rows called a window and returns a column that is included with the other selected columns. The window becomes a partition on the table and allows the rows to retain their details while providing an aggregate. That is what makes the window function different from aggregates, even though, in some cases, it is evaluating an aggregate.

Here is a partial list of the window functions:

  • Ranking:
    • ROW_NUMBER
    • RANK
    • DENSE_RANK
    • NTILE
    • PERCENT_RANK
    • CUME_DISTLEAD
    • FIRST_VALUE
    • LAST_VALUE
    • COUNT
    • PERCENTILE_CONT
    • PERCENTILE_DIST
  • Value:
    • LAG
  • Aggregate:
    • AVG
    • SUM
    • MAX/MIN

Next, we will look at the structure of the window functions and the required clauses to create them.

Using a window function in a query

To use a window function in a query, you just include it as a column in the query definition. Every window function requires an OVER clause and optionally can include a PARTITION BY clause and an ORDER BY clause, which is...

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