1. Introduction to Window Functions
Kathi Kellenberger, MVP Linchpin People
auntkathisql.com

2. History
2005: Window functions introduced 2012: Window functions enhanced

3. Agenda What are window functions? Ranking functions Window aggregates
2012 Enhancements: ORDER BY
2012 Enhancements: Framing
Analytic Functions
Offset Functions
Statistical Functions
Making Business Intelligent

4. What are window functions?
Function performs over a SET (window of the results)
How to identify a window function
The OVER clause defines the window
Where to put window functions
SELECT and ORDER BY clauses only
Important!
The FROM, WHERE, GROUP BY and HAVING clauses operate BEFORE the window functions
Partitions NOT the same as GROUP BY

5. Ranking functions Available since 2005 ROW_NUMBER()
A unique # over the window
RANK()
Deals with ties
DENSE_RANK()
NTILE()
Divide rows into buckets

6. ROW_NUMBER() example CustomerID OrderID Total
Row_Number() Over(Order by OrderID) 1
101
100 2
102 40
103 11 3
104
432 4
105
2000 5
106
300 6
107
674 7
108 76 8
109
234 9
110
889 10

7. ROW_NUMBER() example CustomerID OrderID TotalDue
Row_Number() Over(Partition by CustomerID Order by OrderID) 1
100 5
2000 2 6
300 3 40 11 4
432 7
674 9
234 10
889 8 76

8. Ranking Functions
Demo

9. Window aggregate functions
Your favorite aggregates with no GROUP BY Add aggregate function to a non-aggregate query Calculate over the window: the entire result set or partition Pre-2012 functionality NOT optimized for performance

10. Window aggregate example
CustomerID
OrderID
TotalDue
Sum(TotalDue) Over() 1
100
4990 5
2000 6
300 2 40 3 11 4
432 7
674 9
234 10
889 8 76

11. Window aggregate example
CustomerID
OrderID
TotalDue
Sum(TotalDue) Over(Partition by CustomerID) 1
100
2400 5
2000 6
300 2 40 51 3 11 4
432 7
674
1797 9
234 10
889 8 76
310

12. Window Aggregates
Demo

13. 2012 enhancements
ORDER BY clause added to window aggregates Performance optimization Even further define the window with ROWS and RANGE: FRAMING

14. Window aggregate ORDER BY example
CustomerID
OrderID
TotalDue
Sum(TotalDue) Over(Order by OrderID) 1
100 2 40
140 3 11
151 4
432
583 5
2000
2583 6
300
2883 7
674
3557 8 76
3633 9
234
3867 10
889
4756
4990

15. Running Total
Demo

16. FRAME: ROWS and RANGE Further define window
Terms
UNBOUNDED PRECEDING
UNBOUNDED FOLLOWING
CURRENT ROW
# PRECEDING
# FOLLOWING
RANGE is not fully implemented and can hurt performance

17. Framing
Rows between unbounded preceding and current row

18. Framing
Rows between current row and unbounded following

19. Framing
Rows between 2 preceding and current row

20. Framing
Rows between 5 preceding and 2 following

21. Framing
Demo

22. The Analytic Functions
LAG() and LEAD() Look back or look forward
FIRST_VALUE() and LAST_VALUE() The very first or very last
PERCENT_RANK() and CUME_DIST() Calculate ranking
PERCENTILE_DISC() and PERCENTILE_CONT() Given a percent, find the value

23. Analytic Functions
Demo

24. Resources