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Writing Better Queries with Window Functions

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Who am I?

Kathi Kellenberger, MVPPragmatic Works

www.bidn.com/blogs/kathikellenbergerkkellenberger@pragmaticworks.com

@auntkathi

Teaching SSRS and SSRS Master ClassesBeginning SSRS Joes 2 ProsBeginning T-SQL 2012Beginning T-SQL 2008SQL Server MVP Deep Dives (Vol 1)

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History

2005: Window functions introduced

2012: Window functions enhanced

Best resource: Microsoft SQL Server2012 High-Performance T-SQL Using Window Functions by

Itzik Ben-Gan

Agenda

• What are window functions?• Ranking functions• Window aggregates• 2012 Enhancements: ORDER BY• 2012 Enhancements: Framing• Analytic functions

MAKING BUSINESS INTELLIGENT

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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 functionsSELECT 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

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Ranking functions

Available since 2005ROW_NUMBER() A unique # over the windowRANK() Deals with tiesDENSE_RANK() Deals with tiesNTILE() Divide rows into buckets

ROW_NUMBER() example

CustomerID

OrderID

Total Row_Number() Over(Order by OrderID)

1 101 100 12 102 40 22 103 11 33 104 432 41 105 2000 51 106 300 64 107 674 75 108 76 84 109 234 94 110 889 105 110 234 11

ROW_NUMBER() exampleCustomerID OrderID TotalDu

eRow_Number() Over(Partition by CustomerID Order by OrderID)

1 1 100 11 5 2000 21 6 300 32 2 40 12 3 11 23 4 432 14 7 674 14 9 234 24 10 889 35 8 76 15 11 234 2

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Ranking functions: Tuning

Sequence Project Operator

Index: Partition + Order by + Covering

If there is a filter, add filter columns first

Watch out for reverse directionor different ordering

Ranking Functions

Demo

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Window aggregate functions

Your favorite aggregates with no GROUP BYAdd aggregate function to a non-aggregate queryCalculate over the window: the entire result set or

partitionPre-2012 functionality NOT optimized for

performance

Window aggregate exampleCustomerID

OrderID

TotalDue

Sum(TotalDue) Over()

1 1 100 49901 5 2000 49901 6 300 49902 2 40 49902 3 11 49903 4 432 49904 7 674 49904 9 234 49904 10 889 49905 8 76 49905 11 234 4990

Window aggregate exampleCustomerID OrderID TotalDu

eSum(TotalDue) Over(Partition by CustomerID)

1 1 100 24001 5 2000 24001 6 300 24002 2 40 512 3 11 513 4 432 4324 7 674 17974 9 234 17974 10 889 17975 8 76 3105 11 234 310

Window Aggregates

Demo

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2012 enhancements

ORDER BY clauseadded to window aggregates

Performance optimizationEven further define the

window with ROWS and RANGE: FRAMING

Window aggregate ORDER BY example

CustomerID

OrderID

TotalDue Sum(TotalDue) Over(Order by OrderID)

1 1 100 1002 2 40 1402 3 11 1513 4 432 5831 5 2000 25831 6 300 28834 7 674 35575 8 76 36334 9 234 38674 10 889 47565 11 234 4990

Running Total

Demo

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FRAME: ROWS and RANGE

Further define window Terms

UNBOUNDED PRECEDINGUNBOUNDED FOLLOWINGCURRENT ROW# PRECEDING# FOLLOWING

RANGE is not fully implementedand can hurt performance

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Framing

Rows between unbounded preceding and current row

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Framing

Rows between current row and unbounded following

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Framing

Rows between 2 preceding and current row

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Framing

Rows between 5 precedingand 2 following

Framing

Demo

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

Analytic Functions

Demo