ADVANCE T-SQL: WINDOW

FUNCTIONS

Rahman Wehelie7/16/2013ITC 226

WINDOWING

Window Function belong to a type of function called 'set function‘

Window is used to refer to set of rows that the function works on

Window were added to SQL:2003 - the fifth revision of the SQL database query language.

other DBMSs such as Oracle, Sybase and DB2 have had support for window functions

SQL Server has had only a partial implementation until SQL 2012

You implement window functions as part of a query’s SELECT expression

MAIN BENEFIT

A big benefits of window functions is that we can access the detail of the rows from an aggregation

GOCREATE TABLE Table (ID INT, Value Numeric(18,2))GO

INSERT INTO Table (ID, Value) VALUES(1, 50.3), (1, 123.3), (1, 132.9),      (2, 50.3), (2, 123.3), (2, 132.9), (2, 88.9),      (3, 50.3), (3, 123.3);GO

AGGREGATION

If we sum the value column by conventional GROUP By

SELECT ID, SUM(Value)  FROM TableGROUP BY ID;

CONT…

Here is the set that SUM aggregation function worked on

Because we applied the aggregation function in the column value, grouping the results by ID, we the lose the details of the data

ROW DETAILS

Suppose you need to write a query to return the total /average/quantity value of sales for each ID, and still return the actual values of the rows

SELECT ID,       Value,       SUM(Value) AS "Sum"       AVG(Value) AS "Avg"       COUNT(Value) AS "Quantity"   FROM TableGROUP BY ID;

Column 'Table.Value' is invalid in the select list because it is not contained in either an aggregate function or the GROUP BY clause

it is against the way that aggregations work

OVER() CLAUSE

A commonly used alternative is to write every aggregation into a subquery

The clause OVER() allows us to access the details of the rows that have been aggregated.

SELECT ID,       Value,       SUM(Value) OVER() AS "Sum"       AVG(Value) OVER() AS "Avg"       COUNT(Value) OVER() AS "Quantity"   FROM Table

NEW WINDOW OF DATA - PARTITION BY

Suppose you want the aggregate the data grouped by ID

To do this, use the clause PARTITION BY clause

SELECT ID, Value,  SUM(Value) OVER(PARTITION BY ID) AS "Sum"  AVG(Value) OVER(PARTITION BY ID) AS "Avg"COUNT(Value) OVER(PARTITION BY ID) AS "Quantity"  FROM Table

CONT..

ROW_NUMBER, RANK, DENSE_RANK AND NTILE

To test the functions, let's create a table called Table1

GOCREATE TABLE Table1 (Col1 INT)GO

INSERT INTO Tab1 VALUES(5), (5), (3) , (1)GO

ROW_NUMBER()

The ROW_NUMBER function is used to generate a sequence of numbers based on a set in a specific order.

-- RowNumberSELECT Col1,        ROW_NUMBER() OVER(ORDER BY Col1 DESC) AS "ROW_NUMBER()"     FROM Table1

RANK() & DENSE_RANK()

Returns the rank of each row within the partition of a result set.

The rank of a row is one plus the number of ranks that come before the row in question.

Rank() returns the result with a GAP after a tie, whereas the function DENSE_RANK doesn’t.

EXAMPLE

-- RankSELECT Col1,        RANK() OVER(ORDER BY Col1 DESC) AS "RANK()"   FROM Table1GO

-- Dense_RankSELECT Col1,        DENSE_RANK() OVER(ORDER BY Col1 DESC) AS "DENSE_RANK"   FROM Table1

NTILE()

The NTILE function is used for calculating summary statistics

Distributes the rows in an ordered partition into a specified number of groups.

The groups are numbered, starting at one. For each row, NTILE returns the number of the group to which the row belongs.

NTILE EXAMPLE

-- NTILESELECT Col1,        NTILE(3) OVER(ORDER BY Col1 DESC) AS "NTILE(3)"   FROM Table1

We can see that 4 rows were divided by 3, the remaining row is added in the initial group

-- NTILESELECT Col1,        NTILE(2) OVER(ORDER BY Col1 DESC) AS "NTILE(2)"  FROM Table1

In the next example, there are no remained rows