# GROUP BY

# Simple Grouping

Orders Table

CustomerId	ProductId	Quantity	Price
1	2	5	100
1	3	2	200
1	4	1	500
2	1	4	50
3	5	6	700

When grouping by a specific column, only unique values of this column are returned.

SELECT customerId
FROM orders
GROUP BY customerId;

Return value:

customerId
1
2
3

Aggregate functions like count() apply to each group and not to the complete table:

SELECT customerId, 
       COUNT(productId) as numberOfProducts,
       sum(price) as totalPrice
FROM orders
GROUP BY customerId;

Return value:

customerId	numberOfProducts	totalPrice
1	3	800
2	1	50
3	1	700

# GROUP BY multiple columns

One might want to GROUP BY more than one column

declare @temp table(age int, name varchar(15))

insert into @temp
select 18, 'matt' union all
select 21, 'matt' union all
select 21, 'matt' union all
select 18, 'luke' union all
select 18, 'luke' union all
select 21, 'luke' union all
select 18, 'luke' union all
select 21, 'luke'

SELECT Age, Name, count(1) count
FROM @temp 
GROUP BY Age, Name

will group by both age and name and will produce:

Age	Name	count
18	luke	3
21	luke	2
18	matt	1
21	matt	2

# GROUP BY with ROLLUP and CUBE

The ROLLUP operator is useful in generating reports that contain subtotals and totals.

CUBE generates a result set that shows aggregates for all combinations of values in the selected columns.

SELECT CASE WHEN (GROUPING(Item) = 1) THEN 'ALL'
            ELSE ISNULL(Item, 'UNKNOWN')
       END AS Item,
       CASE WHEN (GROUPING(Color) = 1) THEN 'ALL'
            ELSE ISNULL(Color, 'UNKNOWN')
       END AS Color,
       SUM(Quantity) AS QtySum
FROM Inventory
GROUP BY Item, Color WITH ROLLUP

Item                 Color                QtySum                     
-------------------- -------------------- -------------------------- 
Chair                Blue                 101.00                     
Chair                Red                  210.00                     
Chair                ALL                  311.00                     
Table                Blue                 124.00                     
Table                Red                  223.00                     
Table                ALL                  347.00                     
ALL                  ALL                  658.00

(7 row(s) affected)

If the ROLLUP keyword in the query is changed to CUBE, the CUBE result set is the same, except these two additional rows are returned at the end:

ALL                  Blue                 225.00                     
ALL                  Red                  433.00

https://technet.microsoft.com/en-us/library/ms189305(v=sql.90).aspx (opens new window)

# Group by with multiple tables, multiple columns

Group by is often used with join statement. Let's assume we have two tables. The first one is the table of students:

Id	Full Name	Age
1	Matt Jones	20
2	Frank Blue	21
3	Anthony Angel	18

Second table is the table of subject each student can take:

Subject_Id	Subject
1	Maths
2	P.E.
3	Physics

And because one student can attend many subjects and one subject can be attended by many students (therefore N:N relationship) we need to have third "bounding" table. Let's call the table Students_subjects:

Subject_Id	Student_Id
1	1
2	2
2	1
3	2
1	3
1	1

Now lets say we want to know the number of subjects each student is attending. Here the standalone GROUP BY statement is not sufficient as the information is not available through single table. Therefore we need to use GROUP BY with the JOIN statement:

Select Students.FullName, COUNT(Subject Id) as SubjectNumber FROM Students_Subjects
LEFT JOIN Students
ON Students_Subjects.Student_id = Students.Id
GROUP BY Students.FullName

The result of the given query is as follows:

FullName	SubjectNumber
Matt Jones	3
Frank Blue	2
Anthony Angel	1

For an even more complex example of GROUP BY usage, let's say student might be able to assign the same subject to his name more than once (as shown in table Students_Subjects). In this scenario we might be able to count number of times each subject was assigned to a student by GROUPing by more than one column:

SELECT Students.FullName, Subjects.Subject,
COUNT(Students_subjects.Subject_id) AS NumberOfOrders
FROM ((Students_Subjects
INNER JOIN Students
ON Students_Subjcets.Student_id=Students.Id)
INNER JOIN Subjects
ON Students_Subjects.Subject_id=Subjects.Subject_id)
GROUP BY Fullname,Subject

This query gives the following result:

FullName	Subject	SubjectNumber
Matt Jones	Maths	2
Matt Jones	P.E	1
Frank Blue	P.E	1
Frank Blue	Physics	1
Anthony Angel	Maths	1

# HAVING

Because the WHERE clause is evaluated before GROUP BY, you cannot use WHERE to pare down results of the grouping (typically an aggregate function, such as COUNT(*)). To meet this need, the HAVING clause can be used.

For example, using the following data:

DECLARE @orders TABLE(OrderID INT, Name NVARCHAR(100))

INSERT INTO @orders VALUES
( 1, 'Matt' ),
( 2, 'John' ),
( 3, 'Matt' ),
( 4, 'Luke' ),
( 5, 'John' ),
( 6, 'Luke' ),
( 7, 'John' ),
( 8, 'John' ),
( 9, 'Luke' ),
( 10, 'John' ),
( 11, 'Luke' )

If we want to get the number of orders each person has placed, we would use

SELECT Name, COUNT(*) AS 'Orders'
FROM @orders
GROUP BY Name

and get

Name	Orders
Matt	2
John	5
Luke	4

However, if we want to limit this to individuals who have placed more than two orders, we can add a HAVING clause.

SELECT Name, COUNT(*) AS 'Orders'
FROM @orders
GROUP BY Name
HAVING COUNT(*) > 2

will yield

Name	Orders
John	5
Luke	4

Note that, much like GROUP BY, the columns put in HAVING must exactly match their counterparts in the SELECT statement. If in the above example we had instead said

SELECT Name, COUNT(DISTINCT OrderID)

our HAVING clause would have to say

HAVING COUNT(DISTINCT OrderID) > 2

← OVER Clause ORDER BY →