SQL HAVING

SQL Group By

SQL Union

HAVING is like WHERE but operates on grouped records.

HAVING requires that a GROUP BY clause is present.

Groups that meet the HAVING criteria will be returned.

HAVING is used with aggregrates: COUNT, MAX, SUM, etc.

Example

#

List all countries with more than 2 suppliers.

SELECT Country, COUNT(Id) AS Suppliers
  FROM Supplier
 GROUP BY Country
HAVING COUNT(Id) > 2

Result: 3 records

Country	Suppliers
France	3
Germany	3
USA	4

SQL Group By

SQL Union

Syntax

#

HAVING syntax.

SELECT column-names
  FROM table-name
 WHERE condition
 GROUP BY column-names
HAVING condition

HAVING syntax with ORDER BY.

SELECT column-names
  FROM table-name
 WHERE condition
 GROUP BY column-names
HAVING condition
 ORDER BY column-names

More Examples

#

HAVING with COUNT

CUSTOMER
Id
FirstName
LastName
City
Country
Phone

Problem: List the number of customers in each country. Only include countries with more than 10 customers.

SELECT Country, COUNT(Id) AS Customers
  FROM Customer
 GROUP BY Country
HAVING COUNT(Id) > 10

Result: 3 records

Country	Customers
France	11
Germany	11
USA	13

HAVING and ORDER BY

CUSTOMER
Id
FirstName
LastName
City
Country
Phone

Problem: List the number of customers in each country, except the USA, sorted high to low. Only include countries with 9 or more customers.

SELECT Country, COUNT(Id) AS Customers
  FROM Customer
 WHERE Country <> 'USA'
 GROUP BY Country
HAVING COUNT(Id) >= 9
 ORDER BY COUNT(Id) DESC

Result: 3 records

Country	Customers
France	11
Germany	11
Brazil	9

HAVING with AVG BETWEEN

ORDER
Id
OrderDate
OrderNumber
CustomerId
TotalAmount

CUSTOMER
Id
FirstName
LastName
City
Country
Phone

Problem: List customer with average orders between $1000 and $1200.

SELECT FirstName, LastName, 
       CONVERT(DECIMAL(10,2), AVG(TotalAmount)) AS 'Average  Order'
  FROM [Order] O 
  JOIN Customer C ON O.CustomerId = C.Id
 GROUP BY FirstName, LastName
HAVING AVG(TotalAmount) BETWEEN 1000 AND 1200

Note: CONVERT formats the average value to 2 decimals.

Result: 10 records

FirstName	LastName	Average Order
Miguel	Angel Paolino	1081.22
Isabel	de Castro	1063.42
Alexander	Feuer	1008.44
Thomas	Hardy	1062.04
Pirkko	Koskitalo	1107.81
Janete	Limeira	1174.95
Antonio	Moreno	1073.62
Rita	Müller	1065.39
José	Pedro Freyre	1183.01
Carine	Schmitt	1057.39