SQL Aggregate Functions
SQL aggregate functions return a single value, calculated from values in a column.
Useful aggregate functions:
- AVG() - Returns the average value
- COUNT() - Returns the number of rows
- FIRST() - Returns the first value
- LAST() - Returns the last value
- MAX() - Returns the largest value
- MIN() - Returns the smallest value
- SUM() - Returns the sum
SQL Scalar functions
SQL scalar functions return a single value, based on the input value.
Useful scalar functions:
- UCASE() - Converts a field to upper case
- LCASE() - Converts a field to lower case
- MID() - Extract characters from a text field
- LEN() - Returns the length of a text field
- ROUND() - Rounds a numeric field to the number of
decimals specified - NOW() - Returns the current system date and time
- FORMAT() - Formats how a field is to be displayed
Tip: The aggregate functions and the scalar functions will be explained in details in the next chapters.
The AVG() Function
The AVG() function returns the average value of a numeric column.
SQL AVG() Syntax
SELECT AVG(column_name) FROM table_name |
SQL AVG() Example
We have the following "Orders" table:
O_Id | OrderDate | OrderPrice | Customer |
---|---|---|---|
1 | 2008/11/12 | 1000 | Hansen |
2 | 2008/10/23 | 1600 | Nilsen |
3 | 2008/09/02 | 700 | Hansen |
4 | 2008/09/03 | 300 | Hansen |
5 | 2008/08/30 | 2000 | Jensen |
6 | 2008/10/04 | 100 | Nilsen |
Now we want to find the average value of the "OrderPrice" fields.
We use the following SQL statement:
SELECT AVG(OrderPrice) AS OrderAverage FROM Orders |
The result-set will look like this:
OrderAverage |
---|
950 |
Now we want to find the customers that have an OrderPrice value higher than the average OrderPrice value.
We use the following SQL statement:
SELECT Customer FROM Orders WHERE OrderPrice>(SELECT AVG(OrderPrice) FROM Orders) |
The result-set will look like this:
Customer |
---|
Hansen |
Nilsen |
Jensen |
The COUNT() function returns the number of rows that matches a specified criteria.
SQL COUNT(column_name) Syntax
The COUNT(column_name) function returns the number of values (NULL values will not be counted) of the specified column:
SELECT COUNT(column_name) FROM table_name |
SQL COUNT(*) Syntax
The COUNT(*) function returns the number of records in a table:
SELECT COUNT(*) FROM table_name |
SQL COUNT(DISTINCT column_name) Syntax
The COUNT(DISTINCT column_name) function returns the number of distinct
values of the specified column:
SELECT COUNT(DISTINCT column_name) FROM table_name |
Note: COUNT(DISTINCT) works with ORACLE and Microsoft SQL Server, but not with Microsoft Access.
SQL COUNT(column_name) Example
We have the following "Orders" table:
O_Id | OrderDate | OrderPrice | Customer |
---|---|---|---|
1 | 2008/11/12 | 1000 | Hansen |
2 | 2008/10/23 | 1600 | Nilsen |
3 | 2008/09/02 | 700 | Hansen |
4 | 2008/09/03 | 300 | Hansen |
5 | 2008/08/30 | 2000 | Jensen |
6 | 2008/10/04 | 100 | Nilsen |
Now we want to count the number of orders from "Customer Nilsen".
We use the following SQL statement:
SELECT COUNT(Customer) AS CustomerNilsen FROM Orders WHERE Customer='Nilsen' |
The result of the SQL statement above will be 2, because the customer Nilsen has made 2 orders in total:
CustomerNilsen |
---|
2 |
SQL COUNT(*) Example
If we omit the WHERE clause, like this:
SELECT COUNT(*) AS NumberOfOrders FROM Orders |
The result-set will look like this:
NumberOfOrders |
---|
6 |
which is the total number of rows in the table.
SQL COUNT(DISTINCT column_name) Example
Now we want to count the number of unique customers in the "Orders" table.
We use the following SQL statement:
SELECT COUNT(DISTINCT Customer) AS NumberOfCustomers FROM Orders |
The result-set will look like this:
NumberOfCustomers |
---|
3 |
which is the number of unique customers (Hansen, Nilsen, and Jensen) in the "Orders" table.
The FIRST() Function
The FIRST() function returns the first value of the selected column.
SQL FIRST() Syntax
SELECT FIRST(column_name) FROM table_name |
SQL FIRST() Example
We have the following "Orders" table:
O_Id | OrderDate | OrderPrice | Customer |
---|---|---|---|
1 | 2008/11/12 | 1000 | Hansen |
2 | 2008/10/23 | 1600 | Nilsen |
3 | 2008/09/02 | 700 | Hansen |
4 | 2008/09/03 | 300 | Hansen |
5 | 2008/08/30 | 2000 | Jensen |
6 | 2008/10/04 | 100 | Nilsen |
Now we want to find the first value of the "OrderPrice" column.
We use the following SQL statement:
SELECT FIRST(OrderPrice) AS FirstOrderPrice FROM Orders |
Tip: Workaround if FIRST() function is not supported:
SELECT OrderPrice FROM Orders ORDER BY O_Id LIMIT 1 |
The result-set will look like this:
FirstOrderPrice |
---|
1000 |
The LAST() Function
The LAST() function returns the last value of the selected column.
SQL LAST() Syntax
SELECT LAST(column_name) FROM table_name |
SQL LAST() Example
We have the following "Orders" table:
O_Id | OrderDate | OrderPrice | Customer |
---|---|---|---|
1 | 2008/11/12 | 1000 | Hansen |
2 | 2008/10/23 | 1600 | Nilsen |
3 | 2008/09/02 | 700 | Hansen |
4 | 2008/09/03 | 300 | Hansen |
5 | 2008/08/30 | 2000 | Jensen |
6 | 2008/10/04 | 100 | Nilsen |
Now we want to find the last value of the "OrderPrice" column.
We use the following SQL statement:
SELECT LAST(OrderPrice) AS LastOrderPrice FROM Orders |
Tip: Workaround if LAST() function is not supported:
SELECT OrderPrice FROM Orders ORDER BY O_Id DESC LIMIT 1 |
The result-set will look like this:
LastOrderPrice |
---|
100 |
The MAX() Function
The MAX() function returns the largest value of the selected column.
SQL MAX() Syntax
SELECT MAX(column_name) FROM table_name |
SQL MAX() Example
We have the following "Orders" table:
O_Id | OrderDate | OrderPrice | Customer |
---|---|---|---|
1 | 2008/11/12 | 1000 | Hansen |
2 | 2008/10/23 | 1600 | Nilsen |
3 | 2008/09/02 | 700 | Hansen |
4 | 2008/09/03 | 300 | Hansen |
5 | 2008/08/30 | 2000 | Jensen |
6 | 2008/10/04 | 100 | Nilsen |
Now we want to find the largest value of the "OrderPrice" column.
We use the following SQL statement:
SELECT MAX(OrderPrice) AS LargestOrderPrice FROM Orders |
The result-set will look like this:
LargestOrderPrice |
---|
2000 |
The MIN() Function
The MIN() function returns the smallest value of the selected column.
SQL MIN() Syntax
SELECT MIN(column_name) FROM table_name |
SQL MIN() Example
We have the following "Orders" table:
O_Id | OrderDate | OrderPrice | Customer |
---|---|---|---|
1 | 2008/11/12 | 1000 | Hansen |
2 | 2008/10/23 | 1600 | Nilsen |
3 | 2008/09/02 | 700 | Hansen |
4 | 2008/09/03 | 300 | Hansen |
5 | 2008/08/30 | 2000 | Jensen |
6 | 2008/10/04 | 100 | Nilsen |
Now we want to find the smallest value of the "OrderPrice" column.
We use the following SQL statement:
SELECT MIN(OrderPrice) AS SmallestOrderPrice FROM Orders |
The result-set will look like this:
SmallestOrderPrice |
---|
100 |
The SUM() Function
The SUM() function returns the total sum of a numeric column.
SQL SUM() Syntax
SELECT SUM(column_name) FROM table_name |
SQL SUM() Example
We have the following "Orders" table:
O_Id | OrderDate | OrderPrice | Customer |
---|---|---|---|
1 | 2008/11/12 | 1000 | Hansen |
2 | 2008/10/23 | 1600 | Nilsen |
3 | 2008/09/02 | 700 | Hansen |
4 | 2008/09/03 | 300 | Hansen |
5 | 2008/08/30 | 2000 | Jensen |
6 | 2008/10/04 | 100 | Nilsen |
Now we want to find the sum of all "OrderPrice" fields".
We use the following SQL statement:
SELECT SUM(OrderPrice) AS OrderTotal FROM Orders |
The result-set will look like this:
OrderTotal |
---|
5700 |
The GROUP BY Statement
The GROUP BY statement is used in conjunction with the aggregate functions to group the result-set by one or more columns.
SQL GROUP BY Syntax
SELECT column_name, aggregate_function(column_name) FROM table_name WHERE column_name operator value GROUP BY column_name |
SQL GROUP BY Example
We have the following "Orders" table:
O_Id | OrderDate | OrderPrice | Customer |
---|---|---|---|
1 | 2008/11/12 | 1000 | Hansen |
2 | 2008/10/23 | 1600 | Nilsen |
3 | 2008/09/02 | 700 | Hansen |
4 | 2008/09/03 | 300 | Hansen |
5 | 2008/08/30 | 2000 | Jensen |
6 | 2008/10/04 | 100 | Nilsen |
Now we want to find the total sum (total order) of each customer.
We will have to use the GROUP BY statement to group the customers.
We use the following SQL statement:
SELECT Customer,SUM(OrderPrice) FROM Orders GROUP BY Customer |
The result-set will look like this:
Customer | SUM(OrderPrice) |
---|---|
Hansen | 2000 |
Nilsen | 1700 |
Jensen | 2000 |
Nice! Isn't it? :)
Let's see what happens if we omit the GROUP BY statement:
SELECT Customer,SUM(OrderPrice) FROM Orders |
The result-set will look like this:
Customer | SUM(OrderPrice) |
---|---|
Hansen | 5700 |
Nilsen | 5700 |
Hansen | 5700 |
Hansen | 5700 |
Jensen | 5700 |
Nilsen | 5700 |
The result-set above is not what we wanted.
Explanation of why the above SELECT statement cannot be used: The SELECT statement above has two columns specified (Customer and SUM(OrderPrice).
The "SUM(OrderPrice)" returns a single value (that is the total sum of the "OrderPrice" column), while "Customer" returns 6 values
(one value for each row in the "Orders" table). This will therefore not give us the correct result. However, you have seen that the GROUP BY statement solves this problem.
GROUP BY More Than One Column
We can also use the GROUP BY statement on more than one column, like this:
SELECT Customer,OrderDate,SUM(OrderPrice) FROM Orders GROUP BY Customer,OrderDate |
The HAVING Clause
The HAVING clause was added to SQL because the WHERE keyword could not be used with aggregate functions.
SQL HAVING Syntax
SELECT column_name, aggregate_function(column_name) FROM table_name WHERE column_name operator value GROUP BY column_name HAVING aggregate_function(column_name) operator value |
SQL HAVING Example
We have the following "Orders" table:
O_Id | OrderDate | OrderPrice | Customer |
---|---|---|---|
1 | 2008/11/12 | 1000 | Hansen |
2 | 2008/10/23 | 1600 | Nilsen |
3 | 2008/09/02 | 700 | Hansen |
4 | 2008/09/03 | 300 | Hansen |
5 | 2008/08/30 | 2000 | Jensen |
6 | 2008/10/04 | 100 | Nilsen |
Now we want to find if any of the customers have a total order of less than 2000.
We use the following SQL statement:
SELECT Customer,SUM(OrderPrice) FROM Orders GROUP BY Customer HAVING SUM(OrderPrice)<2000 |
The result-set will look like this:
Customer | SUM(OrderPrice) |
---|---|
Nilsen | 1700 |
Now we want to find if the customers "Hansen" or "Jensen" have a total order of more than 1500.
We add an ordinary WHERE clause to the SQL statement:
SELECT Customer,SUM(OrderPrice) FROM Orders WHERE Customer='Hansen' OR Customer='Jensen' GROUP BY Customer HAVING SUM(OrderPrice)>1500 |
The result-set will look like this:
Customer | SUM(OrderPrice) |
---|---|
Hansen | 2000 |
Jensen | 2000 |
The UCASE() Function
The UCASE() function converts the value of a field to uppercase.
SQL UCASE() Syntax
SELECT UCASE(column_name) FROM table_name |
Syntax for SQL Server
SELECT UPPER(column_name) FROM table_name |
SQL UCASE() Example
We have the following "Persons" table:
P_Id | LastName | FirstName | Address | City |
---|---|---|---|---|
1 | Hansen | Ola | Timoteivn 10 | Sandnes |
2 | Svendson | Tove | Borgvn 23 | Sandnes |
3 | Pettersen | Kari | Storgt 20 | Stavanger |
Now we want to select the content of the "LastName" and "FirstName" columns above, and convert the "LastName" column to uppercase.
We use the following SELECT statement:
SELECT UCASE(LastName) as LastName,FirstName FROM Persons |
The result-set will look like this:
LastName | FirstName |
---|---|
HANSEN | Ola |
SVENDSON | Tove |
PETTERSEN | Kari |
The LCASE() Function
The LCASE() function converts the value of a field to lowercase.
SQL LCASE() Syntax
SELECT LCASE(column_name) FROM table_name |
Syntax for SQL Server
SELECT LOWER(column_name) FROM table_name |
SQL LCASE() Example
We have the following "Persons" table:
P_Id | LastName | FirstName | Address | City |
---|---|---|---|---|
1 | Hansen | Ola | Timoteivn 10 | Sandnes |
2 | Svendson | Tove | Borgvn 23 | Sandnes |
3 | Pettersen | Kari | Storgt 20 | Stavanger |
Now we want to select the content of the "LastName" and "FirstName" columns above, and convert the "LastName" column to lowercase.
We use the following SELECT statement:
SELECT LCASE(LastName) as LastName,FirstName FROM Persons |
The result-set will look like this:
LastName | FirstName |
---|---|
hansen | Ola |
svendson | Tove |
pettersen | Kari |
The MID() Function
The MID() function is used to extract characters from a text field.
SQL MID() Syntax
SELECT MID(column_name,start[,length]) FROM table_name |
Parameter | Description |
---|---|
column_name | Required. The field to extract characters from |
start | Required. Specifies the starting position (starts at 1) |
length | Optional. The number of characters to return. If omitted, the MID() function returns the rest of the text |
SQL MID() Example
We have the following "Persons" table:
P_Id | LastName | FirstName | Address | City |
---|---|---|---|---|
1 | Hansen | Ola | Timoteivn 10 | Sandnes |
2 | Svendson | Tove | Borgvn 23 | Sandnes |
3 | Pettersen | Kari | Storgt 20 | Stavanger |
Now we want to extract the first four characters of the "City" column above.
We use the following SELECT statement:
SELECT MID(City,1,4) as SmallCity FROM Persons |
The result-set will look like this:
SmallCity |
---|
Sand |
Sand |
Stav |
The LEN() Function
The LEN() function returns the length of the value in a text field.
SQL LEN() Syntax
SELECT LEN(column_name) FROM table_name |
SQL LEN() Example
We have the following "Persons" table:
P_Id | LastName | FirstName | Address | City |
---|---|---|---|---|
1 | Hansen | Ola | Timoteivn 10 | Sandnes |
2 | Svendson | Tove | Borgvn 23 | Sandnes |
3 | Pettersen | Kari | Storgt 20 | Stavanger |
Now we want to select the length of the values in the "Address" column above.
We use the following SELECT statement:
SELECT LEN(Address) as LengthOfAddress FROM Persons |
The result-set will look like this:
LengthOfAddress |
---|
12 |
9 |
9 |
The ROUND() Function
The ROUND() function is used to round a numeric field to the number of decimals specified.
SQL ROUND() Syntax
SELECT ROUND(column_name,decimals) FROM table_name |
Parameter | Description |
---|---|
column_name | Required. The field to round. |
decimals | Required. Specifies the number of decimals to be returned. |
SQL ROUND() Example
We have the following "Products" table:
Prod_Id | ProductName | Unit | UnitPrice |
---|---|---|---|
1 | Jarlsberg | 1000 g | 10.45 |
2 | Mascarpone | 1000 g | 32.56 |
3 | Gorgonzola | 1000 g | 15.67 |
Now we want to display the product name and the price rounded to the nearest integer.
We use the following SELECT statement:
SELECT ProductName, ROUND(UnitPrice,0) as UnitPrice FROM Products |
The result-set will look like this:
ProductName | UnitPrice |
---|---|
Jarlsberg | 10 |
Mascarpone | 33 |
Gorgonzola | 16 |
The NOW() Function
The NOW() function returns the current system date and time.
SQL NOW() Syntax
SELECT NOW() FROM table_name |
SQL NOW() Example
We have the following "Products" table:
Prod_Id | ProductName | Unit | UnitPrice |
---|---|---|---|
1 | Jarlsberg | 1000 g | 10.45 |
2 | Mascarpone | 1000 g | 32.56 |
3 | Gorgonzola | 1000 g | 15.67 |
Now we want to display the products and prices per today's date.
We use the following SELECT statement:
SELECT ProductName, UnitPrice, Now() as PerDate FROM Products |
The result-set will look like this:
ProductName | UnitPrice | PerDate |
---|---|---|
Jarlsberg | 10.45 | 10/7/2008 11:25:02 AM |
Mascarpone | 32.56 | 10/7/2008 11:25:02 AM |
Gorgonzola | 15.67 | 10/7/2008 11:25:02 AM |
The FORMAT() Function
The FORMAT() function is used to format how a field is to be displayed.
SQL FORMAT() Syntax
SELECT FORMAT(column_name,format) FROM table_name |
Parameter | Description |
---|---|
column_name | Required. The field to be formatted. |
format | Required. Specifies the format. |
SQL FORMAT() Example
We have the following "Products" table:
Prod_Id | ProductName | Unit | UnitPrice |
---|---|---|---|
1 | Jarlsberg | 1000 g | 10.45 |
2 | Mascarpone | 1000 g | 32.56 |
3 | Gorgonzola | 1000 g | 15.67 |
Now we want to display the products and prices per today's date (with today's date displayed in the following format "YYYY-MM-DD").
We use the following SELECT statement:
SELECT ProductName, UnitPrice, FORMAT(Now(),'YYYY-MM-DD') as PerDate FROM Products |
The result-set will look like this:
ProductName | UnitPrice | PerDate |
---|---|---|
Jarlsberg | 10.45 | 2008-10-07 |
Mascarpone | 32.56 | 2008-10-07 |
Gorgonzola | 15.67 | 2008-10-07 |
Quick Reference
SQL Statement | Syntax |
---|---|
AND / OR | SELECT column_name(s) FROM table_name WHERE condition AND|OR condition |
ALTER TABLE | ALTER TABLE table_name ADD column_name datatype or ALTER TABLE table_name |
AS (alias) | SELECT column_name AS column_alias FROM table_name or SELECT column_name |
BETWEEN | SELECT column_name(s) FROM table_name WHERE column_name BETWEEN value1 AND value2 |
CREATE DATABASE | CREATE DATABASE database_name |
CREATE TABLE | CREATE TABLE table_name ( column_name1 data_type, column_name2 data_type, column_name2 data_type, ... ) |
CREATE INDEX | CREATE INDEX index_name ON table_name (column_name) or CREATE UNIQUE INDEX index_name |
CREATE VIEW | CREATE VIEW view_name AS SELECT column_name(s) FROM table_name WHERE condition |
DELETE | DELETE FROM table_name WHERE some_column=some_value or DELETE FROM table_name DELETE * FROM table_name |
DROP DATABASE | DROP DATABASE database_name |
DROP INDEX | DROP INDEX table_name.index_name (SQL Server) DROP INDEX index_name ON table_name (MS Access) DROP INDEX index_name (DB2/Oracle) ALTER TABLE table_name DROP INDEX index_name (MySQL) |
DROP TABLE | DROP TABLE table_name |
GROUP BY | SELECT column_name, aggregate_function(column_name) FROM table_name WHERE column_name operator value GROUP BY column_name |
HAVING | SELECT column_name, aggregate_function(column_name) FROM table_name WHERE column_name operator value GROUP BY column_name HAVING aggregate_function(column_name) operator value |
IN | SELECT column_name(s) FROM table_name WHERE column_name IN (value1,value2,..) |
INSERT INTO | INSERT INTO table_name VALUES (value1, value2, value3,....) or INSERT INTO table_name |
INNER JOIN | SELECT column_name(s) FROM table_name1 INNER JOIN table_name2 ON table_name1.column_name=table_name2.column_name |
LEFT JOIN | SELECT column_name(s) FROM table_name1 LEFT JOIN table_name2 ON table_name1.column_name=table_name2.column_name |
RIGHT JOIN | SELECT column_name(s) FROM table_name1 RIGHT JOIN table_name2 ON table_name1.column_name=table_name2.column_name |
FULL JOIN | SELECT column_name(s) FROM table_name1 FULL JOIN table_name2 ON table_name1.column_name=table_name2.column_name |
LIKE | SELECT column_name(s) FROM table_name WHERE column_name LIKE pattern |
ORDER BY | SELECT column_name(s) FROM table_name ORDER BY column_name [ASC|DESC] |
SELECT | SELECT column_name(s) FROM table_name |
SELECT * | SELECT * FROM table_name |
SELECT DISTINCT | SELECT DISTINCT column_name(s) FROM table_name |
SELECT INTO | SELECT * INTO new_table_name [IN externaldatabase] FROM old_table_name or SELECT column_name(s) |
SELECT TOP | SELECT TOP number|percent column_name(s) FROM table_name |
TRUNCATE TABLE | TRUNCATE TABLE table_name |
UNION | SELECT column_name(s) FROM table_name1 UNION SELECT column_name(s) FROM table_name2 |
UNION ALL | SELECT column_name(s) FROM table_name1 UNION ALL SELECT column_name(s) FROM table_name2 |
UPDATE | UPDATE table_name SET column1=value, column2=value,... WHERE some_column=some_value |
WHERE | SELECT column_name(s) FROM table_name WHERE column_name operator value |
SQL Hosting
If you want your web site to be able to store and display data from a database, your web server should have access to a database system that uses the SQL language.
If your web server will be hosted by an Internet Service Provider (ISP), you will have to look for SQL hosting plans.
The most common SQL hosting databases are MySQL, MS SQL Server, and MS Access.
You can have SQL databases on both Windows and Linux/UNIX operating systems.
Below is an overview of which database system that runs on which OS.
MS SQL Server
Runs only on Windows OS.
MySQL
Runs on both Windows and Linux/UNIX operating systems.
MS Access (recommended only for small websites)
Runs only on Windows OS.
To learn more about web hosting, please visit our Hosting tutorial.