Friday, January 8, 2010

SQL Functions

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

Note 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

Note 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

DROP COLUMN column_name

AS (alias) SELECT column_name AS column_alias

FROM table_name

or

SELECT column_name

FROM table_name  AS table_alias

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

ON table_name (column_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

(Note: Deletes the entire table!!)

DELETE * FROM table_name

(Note: Deletes the entire table!!)

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

(column1, column2, column3,...)

VALUES (value1, value2, value3,....)

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)

INTO new_table_name [IN externaldatabase]

FROM old_table_name

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.