SQL Server Windowing Functions

Transcription

1 SQL Server Windowing Functions Enrique Catalá Bañuls Mentor, SolidQ MAP 2012 Microsoft Technical Ranger Microsoft Certified Trainer

2 Enrique Catalá Bañuls Computer engineer Mentor at SolidQ in the relational engine team Microsoft Technical Ranger Microsoft Active Professional Microsoft Certified Trainer

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5 Objectives of this session Introduction The past, the present and the future Window Functions Why do we need window functions? Syntax Performance Why almost complete? Q&A 5

6 Window Functions Window function function applied to a set of rows defined by a window descriptor and returns a single value for each row from the underlying query Window descriptor Define which rows will be used with the function

7 Objectives of this session Introduction The past, the present and the future Window Functions Why do we need window functions? Syntax Performance Why almost complete? Q&A 7

8 The past, the present and the future The SQL 2000 way SQL Server 2000 does not provide any syntax to support windowing functions The SQL 2005 way SQL Server 2005 to 2008R2 introduced a partial implementation of the windowing functions using the OVER clause The SQL 2012 way SQL Server 2012 will have an almost complete implementation of the windowing functions

9 The SQL R2 way SQL Server 2005 introduces OVER clause (partially implemented) New window functions o ROW_NUMBER() o RANK() o DENSE_RANK() o NTILE() SQL Server 2008/2008R2 added no new implementations in this particular area

10 The SQL R2 way OVER clause Two different implementations depending on type of windowing Aggregate window functions does not provide the ORDER BY clause

11 The SQL 2012 way SQL Server 2012 are getting close to the full implementation of Windowing functions SQL Server 2012 introduces: OVER clause almost complete o Order by o Window Frame 8 new window functions o LAG(), LEAD() o FIRST_VALUE(), LAST_VALUE() o CUME_DIST() o PERCENT_RANK() o PERCENTILE_DISC(), PERCENTILE_COUNT()

12 OVER clause syntax SQL Server 2005/2008/R2 SQL Server 2012

13 Objectives of this session Introduction The past, the present and the future Window Functions Why do we need window functions? Syntax Performance Why almost complete? Q&A 13

14 Why do we need windows functions? Why do we need windows functions? What if we want to get the sum and the value column? (group and detail) select Select id_table, sum(value) value, as [sum(value)] from sum(value) table1 group as [sum(value)] by id_table from table1 group by id_table Msg 8120, Level 16, State 1, Line 1 id_table value value sum(value) SUM(value) Column 'table1.value' is invalid in the select list because it is not contained in either an aggregate function or the GROUP BY clause. If we are in SQL 2005/2008/2008R2 am i correct with this approach?

15 Why do we need windows functions? Now we know that the OVER clause exists This must be our solution select id_table, value, sum(value) over(partition by id_table) from table1 id_table value sum(value)

16 New syntax to solve old problems Partitioning Ordering Slicing/framing

17 Key concepts: All together Partition UNBOUNDED PRECEDING CURRENT ROW UNBOUNDED FOLLOWING

18 Key concepts

19 Key concepts: Partition Partition is like a group of rows with similar characteristics inside a set

20 Key concepts: Partition Partition is like a group of rows with similar characteristics inside a set

21 Key concepts: Slicing/Framing RANGE/ROWS ROWS RANGE BETWEEN <B1> AND <B2> ROWS RANGE <B1>

22 Key concepts: Slicing/Framing B1 and B2 can be UNBOUNDED PRECEDING UNBOUNDED FOLLOWING CURRENT ROW For ROWS clause only o <scalar expression> PRECEDING o <sclara expression> FOLLOWING Note B1 <= B2 or NULL will be returned o Except in COUNT() that 0 will be returned

23 Key concepts: All together Partition UNBOUNDED PRECEDING CURRENT ROW UNBOUNDED FOLLOWING

24 New windowing functions New analytic functions in SQL 2012 offset LAG() LEAD() FIRST_VALUE() LAST_VALUE() Distribution PERCENT_RANK() CUME_DIST() PERCENTILE_CONT() PERCENTILE_DIST()

25 Basics on framing, RANGE vs ROWS, new window functions DEMO 1: NEW FUNCTIONS AND SYNTAX

26 Objectives of this session Introduction The past, the present and the future Window Functions Why do we need window functions? Syntax Performance Why almost complete? Q&A 26

27 Objectives of this session Introduction The past, the present and the future Window Functions Why do we need window functions? Syntax Performance Why almost complete? Q&A 27

28 Performance: IN-MEMORY vs ON DISK Directly affected by Window Spool Operator Used to store the framing data In-memory vs disk-based worktable In-memory worktable Fastest Prerequisites: Framing defined using ROWS and working with <10k rows Disk-based worktable Default Used when the window was defined using RANGE Used when the windows was defined using ROWS and the frame has more than 10k rows

29 Performance: Indexing Index order by the window partitioning elements and then by the order elements Include the rest of the columns Optimized execution operators: 1. Scan 2. Segment 3. Window spool 4. Aggregate

30 Running Totals, in memory vs on disk, DEMO 2: PERFORMANCE

31 Why almost complete? RANGE only supports UNBOUNDED PRECEDING UNBOUNDED FOLLOWING CURRENT ROW Ranking functions does not support framing: ROW_NUMBER, RANK, NTILE,DENSE_RANK, PERCENTILE_DIST, PERCENTILE_CONT Not implemented WINDOW aliases Clauses: NULLs FIRST and NULLs LAST

32 Objectives of this session Introduction The past, the present and the future Window Functions Why do we need window functions? Syntax Performance Why almost complete? Q&A 32

33 THANK YOU! Enrique Catalá Bañuls Mentor, SolidQ MAP 2012 Microsoft Technical Ranger Microsoft Certified Trainer

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