# GROUP BY

Results of a SELECT query can be grouped by one or more columns using the GROUP BY statement: all results with the same value in the grouped columns are aggregated together. This generates a table of partial results, instead of one result. GROUP BY can be used in conjunction with aggregation functions using the HAVING statement to define how non-grouped columns are aggregated.

# Basic GROUP BY example

It might be easier if you think of GROUP BY as "for each" for the sake of explanation. The query below:

SELECT EmpID, SUM (MonthlySalary) 
FROM Employee
GROUP BY EmpID

is saying:

"Give me the sum of MonthlySalary's for each EmpID"

So if your table looked like this:

+-----+-------------+
|EmpID|MonthlySalary|
+-----+-------------+
|1    |200          |
+-----+-------------+
|2    |300          |
+-----+-------------+

Result:

+-+---+
|1|200|
+-+---+
|2|300|
+-+---+

Sum wouldn't appear to do anything because the sum of one number is that number. On the other hand if it looked like this:

+-----+-------------+
|EmpID|MonthlySalary|
+-----+-------------+
|1    |200          |
+-----+-------------+
|1    |300          |
+-----+-------------+
|2    |300          |
+-----+-------------+

Result:

+-+---+
|1|500|
+-+---+
|2|300|
+-+---+

Then it would because there are two EmpID 1's to sum together.

# USE GROUP BY to COUNT the number of rows for each unique entry in a given column

Let's say you want to generate counts or subtotals for a given value in a column.

Given this table, "Westerosians":

Name GreatHouseAllegience
Arya Stark
Cercei Lannister
Myrcella Lannister
Yara Greyjoy
Catelyn Stark
Sansa Stark

Without GROUP BY, COUNT will simply return a total number of rows:

SELECT Count(*) Number_of_Westerosians
FROM Westerosians

returns...

Number_of_Westerosians
6

But by adding GROUP BY, we can COUNT the users for each value in a given column, to return the number of people in a given Great House, say:

SELECT GreatHouseAllegience House, Count(*) Number_of_Westerosians
FROM Westerosians
GROUP BY GreatHouseAllegience

returns...

House Number_of_Westerosians
Stark 3
Greyjoy 1
Lannister 2

It's common to combine GROUP BY with ORDER BY to sort results by largest or smallest category:

SELECT GreatHouseAllegience House, Count(*) Number_of_Westerosians
FROM Westerosians
GROUP BY GreatHouseAllegience
ORDER BY Number_of_Westerosians Desc

returns...

House Number_of_Westerosians
Stark 3
Lannister 2
Greyjoy 1

# Filter GROUP BY results using a HAVING clause

A HAVING clause filters the results of a GROUP BY expression. Note: The following examples are using the Library example database.

Examples:

Return all authors that wrote more than one book (live example).

SELECT
  a.Id,
  a.Name,
  COUNT(*) BooksWritten
FROM BooksAuthors ba
  INNER JOIN Authors a ON a.id = ba.authorid
GROUP BY
  a.Id,
  a.Name
HAVING COUNT(*) > 1    -- equals to HAVING BooksWritten > 1
;

Return all books that have more than three authors (live example).

SELECT
  b.Id,
  b.Title,
  COUNT(*) NumberOfAuthors
FROM BooksAuthors ba
  INNER JOIN Books b ON b.id = ba.bookid
GROUP BY
  b.Id,
  b.Title
HAVING COUNT(*) > 3    -- equals to HAVING NumberOfAuthors > 3
;

# ROLAP aggregation (Data Mining)

# Description

The SQL standard provides two additional aggregate operators. These use the polymorphic value "ALL" to denote the set of all values ​​that an attribute can take. The two operators are:

  • with data cube that it provides all possible combinations than the argument attributes of the clause.
  • with roll up that it provides the aggregates obtained by considering the attributes in order from left to right compared how they are listed in the argument of the clause.

SQL standard versions that support these features: 1999,2003,2006,2008,2011.

# Examples

Consider this table:

Food Brand Total_amount
Pasta Brand1 100
Pasta Brand2 250
Pizza Brand2 300

# With cube

select Food,Brand,Total_amount
from Table
group by Food,Brand,Total_amount with cube

Food Brand Total_amount
Pasta Brand1 100
Pasta Brand2 250
Pasta ALL 350
Pizza Brand2 300
Pizza ALL 300
ALL Brand1 100
ALL Brand2 550
ALL ALL 650

# With roll up

select Food,Brand,Total_amount
from Table
group by Food,Brand,Total_amount with roll up

Food Brand Total_amount
Pasta Brand1 100
Pasta Brand2 250
Pizza Brand2 300
Pasta ALL 350
Pizza ALL 300
ALL ALL 650

# Syntax

  • GROUP BY {
          column-expression
        | ROLLUP ( [ ,...n ] )
        | CUBE ( [ ,...n ] )
        | GROUPING SETS ( [ ,...n ] )
        | () --calculates the grand total
    } [ ,...n ]

  • ::=
          column-expression
        | ( column-expression [ ,...n ] )

  • ::=
          () --calculates the grand total
        |
        | ( [ ,...n ] )

  • ::=

        | ROLLUP ( [ ,...n ] )
        | CUBE ( [ ,...n ] )