SQL Tutorial
SQL (pronounced
"ess-que-el") stands for Structured Query Language. SQL is used to
communicate with a database. According to ANSI (American National Standards
Institute), it is the standard language for relational database management
systems. SQL statements are used to perform tasks such as update data on a
database, or retrieve data from a database. Some common relational database
management systems that use SQL are: Oracle, Sybase, Microsoft SQL Server,
Access, Ingres, etc. Although most database systems use SQL, most of them also
have their own additional proprietary extensions that are usually only used on
their system. However, the standard SQL commands such as "Select",
"Insert", "Update", "Delete", "Create",
and "Drop" can be used to accomplish almost everything that one needs
to do with a database. This tutorial will provide you with the instruction on
the basics of each of these commands as well as allow you to put them to
practice using the SQL Interpreter.
SQL is a standard
language for accessing and manipulating databases.
· SQL can execute queries
against a database
· SQL can retrieve data from a
database
· SQL can insert records in a
database
· SQL can update records in a
database
· SQL can delete records from a
database
· SQL can create new databases
· SQL can create new tables in
a database
· SQL can create stored
procedures in a database
· SQL can create views in a
database
· SQL can set permissions on
tables, procedures, and views
SQL Syntax
Database Tables
A database most often contains one
or more tables. Each table is identified by a name (e.g. "Customers"
or "Orders"). Tables contain records (rows) with data.
Below is an example of a table
called "Persons":
P_Id
|
LastName
|
FirstName
|
Address
|
City
|
1
|
Hansen
|
Ola
|
Timoteivn 10
|
Sandnes
|
2
|
Svendson
|
Tove
|
Borgvn 23
|
Sandnes
|
3
|
Pettersen
|
Kari
|
Storgt 20
|
Stavanger
|
The table above contains three
records (one for each person) and five columns (P_Id, LastName, FirstName,
Address, and City).
SQL Statements
Most of the actions you need to
perform on a database are done with SQL statements.
The following SQL statement will
select all the records in the "Persons" table:
SELECT * FROM Persons
In this tutorial we will teach you
all about the different SQL statements.
Keep in Mind That...
- SQL is not case sensitive
Semicolon after SQL Statements?
Some database systems require a
semicolon at the end of each SQL statement.
Semicolon is the standard way to
separate each SQL statement in database systems that allow more than one SQL
statement to be executed in the same call to the server.
We are using MS Access and SQL
Server 2000 and we do not have to put a semicolon after each SQL statement, but
some database programs force you to use it.
SQL DML and DDL
SQL can be divided into two parts:
The Data Manipulation Language (DML) and the Data Definition Language (DDL).
The query and update commands form
the DML part of SQL:
- SELECT - extracts data from a database
- UPDATE - updates data in a database
- DELETE - deletes data from a database
- INSERT INTO - inserts new data into a database
The DDL part of SQL permits database
tables to be created or deleted. It also defines indexes (keys), specifies
links between tables, and imposes constraints between tables. The most
important DDL statements in SQL are:
- CREATE DATABASE - creates a new database
- ALTER DATABASE - modifies a database
- CREATE TABLE - creates a new table
- ALTER TABLE - modifies a table
- DROP TABLE - deletes a table
- CREATE INDEX -
creates an index (search key)
DROP INDEX - deletes an index
The SQL SELECT Statement
The SELECT statement is used to
select data from a database.
The result is stored in a result
table, called the result-set.
SQL SELECT Syntax
SELECT column_name(s)
FROM table_name
FROM table_name
and
SELECT * FROM table_name
Note: SQL is not
case sensitive. SELECT is the same as select.
An SQL SELECT Example
The "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 columns named "LastName" and "FirstName" from the table
above.
We use the following SELECT
statement:
SELECT LastName,FirstName FROM
Persons
The result-set will look like this:
LastName
|
FirstName
|
Hansen
|
Ola
|
Svendson
|
Tove
|
Pettersen
|
Kari
|
SELECT * Example
Now we want to select all the
columns from the "Persons" table.
We use the following SELECT statement:
SELECT * FROM Persons
Tip: The asterisk (*) is a quick way of selecting all
columns!
The result-set will look like this:
P_Id
|
LastName
|
FirstName
|
Address
|
City
|
1
|
Hansen
|
Ola
|
Timoteivn 10
|
Sandnes
|
2
|
Svendson
|
Tove
|
Borgvn 23
|
Sandnes
|
3
|
Pettersen
|
Kari
|
Storgt 20
|
Stavanger
|
Navigation in a Result-set
Most database software systems allow
navigation in the result-set with programming functions, like:
Move-To-First-Record, Get-Record-Content, Move-To-Next-Record, etc.
The SQL SELECT DISTINCT Statement
In a table, some of the columns may
contain duplicate values. This is not a problem, however, sometimes you will
want to list only the different (distinct) values in a table.
The DISTINCT keyword can be used to
return only distinct (different) values.
SQL SELECT DISTINCT Syntax
SELECT DISTINCT column_name(s)
FROM table_name
FROM table_name
SELECT DISTINCT Example
The "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 only the
distinct values from the column named "City" from the table above.
We use the following SELECT
statement:
SELECT DISTINCT City FROM Persons
The result-set will look like this:
City
|
Sandnes
|
Stavanger
|
The
WHERE Clause
The WHERE clause is used to extract
only those records that fulfill a specified criterion.
SQL WHERE Syntax
SELECT column_name(s)
FROM table_name
WHERE column_name operator value
FROM table_name
WHERE column_name operator value
WHERE Clause Example
The "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 only the
persons living in the city "Sandnes" from the table above.
We use the following SELECT
statement:
SELECT * FROM Persons
WHERE City='Sandnes'
WHERE City='Sandnes'
The result-set will look like this:
P_Id
|
LastName
|
FirstName
|
Address
|
City
|
1
|
Hansen
|
Ola
|
Timoteivn 10
|
Sandnes
|
2
|
Svendson
|
Tove
|
Borgvn 23
|
Sandnes
|
Quotes Around Text Fields
SQL uses single quotes around text
values (most database systems will also accept double quotes).
However, numeric values should not
be enclosed in quotes.
For text values:
This is correct:
SELECT * FROM Persons WHERE FirstName='Tove'
This is wrong:
SELECT * FROM Persons WHERE FirstName=Tove
SELECT * FROM Persons WHERE FirstName='Tove'
This is wrong:
SELECT * FROM Persons WHERE FirstName=Tove
For numeric values:
This is correct:
SELECT * FROM Persons WHERE Year=1965
This is wrong:
SELECT * FROM Persons WHERE Year='1965'
SELECT * FROM Persons WHERE Year=1965
This is wrong:
SELECT * FROM Persons WHERE Year='1965'
Operators Allowed in the WHERE
Clause
With the WHERE clause, the following
operators can be used:
Operator
|
Description
|
=
|
Equal
|
<>
|
Not equal
|
>
|
Greater than
|
<
|
Less than
|
>=
|
Greater than or equal
|
<=
|
Less than or equal
|
BETWEEN
|
Between an inclusive
range
|
LIKE
|
Search for a pattern
|
IN
|
To specify multiple
possible values for a column
|
Note: In some versions of SQL the <> operator may be
written as !=
The AND & OR Operators
The AND operator displays a record
if both the first condition and the second condition is true.
The OR operator displays a record if
either the first condition or the second condition is true.
AND Operator Example
The "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 only the
persons with the first name equal to "Tove" AND the last name equal
to "Svendson":
We use the following SELECT
statement:
SELECT * FROM Persons
WHERE FirstName='Tove'
AND LastName='Svendson'
WHERE FirstName='Tove'
AND LastName='Svendson'
The result-set will look like this:
P_Id
|
LastName
|
FirstName
|
Address
|
City
|
2
|
Svendson
|
Tove
|
Borgvn 23
|
Sandnes
|
OR Operator Example
Now we want to select only the
persons with the first name equal to "Tove" OR the first name equal
to "Ola":
We use the following SELECT
statement:
SELECT * FROM Persons
WHERE FirstName='Tove'
OR FirstName='Ola'
WHERE FirstName='Tove'
OR FirstName='Ola'
The result-set will look like this:
P_Id
|
LastName
|
FirstName
|
Address
|
City
|
1
|
Hansen
|
Ola
|
Timoteivn 10
|
Sandnes
|
2
|
Svendson
|
Tove
|
Borgvn 23
|
Sandnes
|
Combining AND & OR
You can also combine AND and OR (use
parenthesis to form complex expressions).
Now we want to select only the
persons with the last name equal to "Svendson" AND the first name
equal to "Tove" OR to "Ola":
We use the following SELECT
statement:
SELECT * FROM Persons WHERE
LastName='Svendson'
AND (FirstName='Tove' OR FirstName='Ola')
LastName='Svendson'
AND (FirstName='Tove' OR FirstName='Ola')
The result-set will look like this:
P_Id
|
LastName
|
FirstName
|
Address
|
City
|
2
|
Svendson
|
Tove
|
Borgvn 23
|
Sandnes
|
The ORDER BY Keyword
The ORDER BY keyword is used to sort
the result-set by a specified column.
The ORDER BY keyword sort the
records in ascending order by default.
If you want to sort the records in a
descending order, you can use the DESC keyword.
SQL ORDER BY Syntax
SELECT column_name(s)
FROM table_name
ORDER BY column_name(s) ASC|DESC
FROM table_name
ORDER BY column_name(s) ASC|DESC
ORDER BY Example
The "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
|
4
|
Nilsen
|
Tom
|
Vingvn 23
|
Stavanger
|
Now we want to select all the
persons from the table above, however, we want to sort the persons by their
last name.
We use the following SELECT
statement:
SELECT * FROM Persons
ORDER BY LastName
ORDER BY LastName
The result-set will look like this:
P_Id
|
LastName
|
FirstName
|
Address
|
City
|
1
|
Hansen
|
Ola
|
Timoteivn 10
|
Sandnes
|
4
|
Nilsen
|
Tom
|
Vingvn 23
|
Stavanger
|
3
|
Pettersen
|
Kari
|
Storgt 20
|
Stavanger
|
2
|
Svendson
|
Tove
|
Borgvn 23
|
Sandnes
|
ORDER BY DESC Example
Now we want to select all the
persons from the table above, however, we want to sort the persons descending
by their last name.
We use the following SELECT
statement:
SELECT * FROM Persons
ORDER BY LastName DESC
ORDER BY LastName DESC
The result-set will look like this:
P_Id
|
LastName
|
FirstName
|
Address
|
City
|
2
|
Svendson
|
Tove
|
Borgvn 23
|
Sandnes
|
3
|
Pettersen
|
Kari
|
Storgt 20
|
Stavanger
|
4
|
Nilsen
|
Tom
|
Vingvn 23
|
Stavanger
|
1
|
Hansen
|
Ola
|
Timoteivn 10
|
Sandnes
|
The INSERT INTO Statement
The INSERT INTO statement is used to
insert a new row in a table.
SQL INSERT INTO Syntax
It is possible to write the INSERT
INTO statement in two forms.
The first form doesn't specify the
column names where the data will be inserted, only their values:
INSERT INTO table_name
VALUES (value1, value2, value3,...)
VALUES (value1, value2, value3,...)
The second form specifies both the
column names and the values to be inserted:
INSERT INTO table_name (column1,
column2, column3,...)
VALUES (value1, value2, value3,...)
VALUES (value1, value2, value3,...)
SQL INSERT INTO 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 insert a new row in
the "Persons" table.
We use the following SQL statement:
INSERT INTO Persons
VALUES (4,'Nilsen', 'Johan', 'Bakken 2', 'Stavanger')
VALUES (4,'Nilsen', 'Johan', 'Bakken 2', 'Stavanger')
The "Persons" table will
now look like this:
P_Id
|
LastName
|
FirstName
|
Address
|
City
|
1
|
Hansen
|
Ola
|
Timoteivn 10
|
Sandnes
|
2
|
Svendson
|
Tove
|
Borgvn 23
|
Sandnes
|
3
|
Pettersen
|
Kari
|
Storgt 20
|
Stavanger
|
4
|
Nilsen
|
Johan
|
Bakken 2
|
Stavanger
|
Insert Data Only in Specified
Columns
It is also possible to only add data
in specific columns.
The following SQL statement will add
a new row, but only add data in the "P_Id", "LastName" and
the "FirstName" columns:
INSERT INTO Persons (P_Id, LastName,
FirstName)
VALUES (5, 'Tjessem', 'Jakob')
VALUES (5, 'Tjessem', 'Jakob')
The "Persons" table will
now look like this:
P_Id
|
LastName
|
FirstName
|
Address
|
City
|
1
|
Hansen
|
Ola
|
Timoteivn 10
|
Sandnes
|
2
|
Svendson
|
Tove
|
Borgvn 23
|
Sandnes
|
3
|
Pettersen
|
Kari
|
Storgt 20
|
Stavanger
|
4
|
Nilsen
|
Johan
|
Bakken 2
|
Stavanger
|
5
|
Tjessem
|
Jakob
|
The UPDATE Statement
The UPDATE statement is used to
update existing records in a table.
SQL UPDATE Syntax
UPDATE table_name
SET column1=value, column2=value2,...
WHERE some_column=some_value
SET column1=value, column2=value2,...
WHERE some_column=some_value
Note: Notice the WHERE clause in the UPDATE syntax. The
WHERE clause specifies which record or records that should be updated. If you
omit the WHERE clause, all records will be updated!
SQL UPDATE Example
The "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
|
4
|
Nilsen
|
Johan
|
Bakken 2
|
Stavanger
|
5
|
Tjessem
|
Jakob
|
Now we want to update the person
"Tjessem, Jakob" in the "Persons" table.
We use the following SQL statement:
UPDATE Persons
SET Address='Nissestien 67', City='Sandnes'
WHERE LastName='Tjessem' AND FirstName='Jakob'
SET Address='Nissestien 67', City='Sandnes'
WHERE LastName='Tjessem' AND FirstName='Jakob'
The "Persons" table will
now look like this:
P_Id
|
LastName
|
FirstName
|
Address
|
City
|
1
|
Hansen
|
Ola
|
Timoteivn 10
|
Sandnes
|
2
|
Svendson
|
Tove
|
Borgvn 23
|
Sandnes
|
3
|
Pettersen
|
Kari
|
Storgt 20
|
Stavanger
|
4
|
Nilsen
|
Johan
|
Bakken 2
|
Stavanger
|
5
|
Tjessem
|
Jakob
|
Nissestien 67
|
Sandnes
|
SQL UPDATE Warning
Be careful when updating records. If
we had omitted the WHERE clause in the example above, like this:
UPDATE Persons
SET Address='Nissestien 67', City='Sandnes'
SET Address='Nissestien 67', City='Sandnes'
The "Persons" table would
have looked like this:
P_Id
|
LastName
|
FirstName
|
Address
|
City
|
1
|
Hansen
|
Ola
|
Nissestien 67
|
Sandnes
|
2
|
Svendson
|
Tove
|
Nissestien 67
|
Sandnes
|
3
|
Pettersen
|
Kari
|
Nissestien 67
|
Sandnes
|
4
|
Nilsen
|
Johan
|
Nissestien 67
|
Sandnes
|
5
|
Tjessem
|
Jakob
|
Nissestien 67
|
Sandnes
|
The DELETE Statement
The DELETE statement is used to
delete rows in a table.
SQL DELETE Syntax
DELETE FROM table_name
WHERE some_column=some_value
WHERE some_column=some_value
Note: Notice the WHERE clause in the DELETE syntax. The
WHERE clause specifies which record or records that should be deleted. If you
omit the WHERE clause, all records will be deleted!
SQL DELETE Example
The "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
|
4
|
Nilsen
|
Johan
|
Bakken 2
|
Stavanger
|
5
|
Tjessem
|
Jakob
|
Nissestien 67
|
Sandnes
|
Now we want to delete the person
"Tjessem, Jakob" in the "Persons" table.
We use the following SQL statement:
DELETE FROM Persons
WHERE LastName='Tjessem' AND FirstName='Jakob'
WHERE LastName='Tjessem' AND FirstName='Jakob'
The "Persons" table will
now look like this:
P_Id
|
LastName
|
FirstName
|
Address
|
City
|
1
|
Hansen
|
Ola
|
Timoteivn 10
|
Sandnes
|
2
|
Svendson
|
Tove
|
Borgvn 23
|
Sandnes
|
3
|
Pettersen
|
Kari
|
Storgt 20
|
Stavanger
|
4
|
Nilsen
|
Johan
|
Bakken 2
|
Stavanger
|
Delete All Rows
It is possible to delete all rows in
a table without deleting the table. This means that the table structure,
attributes, and indexes will be intact:
DELETE FROM table_name
or
DELETE * FROM table_name
or
DELETE * FROM table_name
Note: Be very careful when deleting records. You cannot undo
this statement!
The TOP Clause
The TOP clause is used to specify
the number of records to return.
The TOP clause can be very useful on
large tables with thousands of records. Returning a large number of records can
impact on performance.
Note: Not all database systems support the TOP clause.
SQL Server Syntax
SELECT TOP number|percent
column_name(s)
FROM table_name
CREATE DATABASE my_db
FROM table_name
SQL SELECT TOP Equivalent in MySQL
and Oracle
MySQL Syntax
SELECT column_name(s)
FROM table_name
LIMIT number
FROM table_name
LIMIT number
Example
SELECT *
FROM Persons
LIMIT 5
FROM Persons
LIMIT 5
Oracle Syntax
SELECT column_name(s)
FROM table_name
WHERE ROWNUM <= number
FROM table_name
WHERE ROWNUM <= number
Example
SELECT *
FROM Persons
WHERE ROWNUM <=5
FROM Persons
WHERE ROWNUM <=5
SQL TOP Example
The "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
|
4
|
Nilsen
|
Tom
|
Vingvn 23
|
Stavanger
|
Now we want to select only the two
first records in the table above.
We use the following SELECT
statement:
SELECT TOP 2 * FROM Persons
The result-set will look like this:
P_Id
|
LastName
|
FirstName
|
Address
|
City
|
1
|
Hansen
|
Ola
|
Timoteivn 10
|
Sandnes
|
2
|
Svendson
|
Tove
|
Borgvn 23
|
Sandnes
|
SQL TOP PERCENT Example
The "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
|
4
|
Nilsen
|
Tom
|
Vingvn 23
|
Stavanger
|
Now we want to select only 50% of
the records in the table above.
We use the following SELECT
statement:
SELECT TOP 50 PERCENT * FROM Persons
The result-set will look like this:
P_Id
|
LastName
|
FirstName
|
Address
|
City
|
1
|
Hansen
|
Ola
|
Timoteivn 10
|
Sandnes
|
2
|
Svendson
|
Tove
|
Borgvn 23
|
Sandnes
|
The LIKE Operator
The LIKE operator is used to search
for a specified pattern in a column.
SQL LIKE Syntax
SELECT column_name(s)
FROM table_name
WHERE column_name LIKE pattern
FROM table_name
WHERE column_name LIKE pattern
LIKE Operator Example
The "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 persons
living in a city that starts with "s" from the table above.
We use the following SELECT
statement:
SELECT * FROM Persons
WHERE City LIKE 's%'
WHERE City LIKE 's%'
The "%" sign can be used
to define wildcards (missing letters in the pattern) both before and after
the pattern.
The result-set will look like this:
P_Id
|
LastName
|
FirstName
|
Address
|
City
|
1
|
Hansen
|
Ola
|
Timoteivn 10
|
Sandnes
|
2
|
Svendson
|
Tove
|
Borgvn 23
|
Sandnes
|
3
|
Pettersen
|
Kari
|
Storgt 20
|
Stavanger
|
Next, we want to select the persons
living in a city that ends with an "s" from the "Persons"
table.
We use the following SELECT
statement:
SELECT * FROM Persons
WHERE City LIKE '%s'
WHERE City LIKE '%s'
The result-set will look like this:
P_Id
|
LastName
|
FirstName
|
Address
|
City
|
1
|
Hansen
|
Ola
|
Timoteivn 10
|
Sandnes
|
2
|
Svendson
|
Tove
|
Borgvn 23
|
Sandnes
|
Next, we want to select the persons
living in a city that contains the pattern "tav" from the
"Persons" table.
We use the following SELECT
statement:
SELECT * FROM Persons
WHERE City LIKE '%tav%'
WHERE City LIKE '%tav%'
The result-set will look like this:
P_Id
|
LastName
|
FirstName
|
Address
|
City
|
3
|
Pettersen
|
Kari
|
Storgt 20
|
Stavanger
|
It is also possible to select the
persons living in a city that does NOT contain the pattern "tav" from
the "Persons" table, by using the NOT keyword.
We use the following SELECT
statement:
SELECT * FROM Persons
WHERE City NOT LIKE '%tav%'
WHERE City NOT LIKE '%tav%'
The result-set will look like this:
P_Id
|
LastName
|
FirstName
|
Address
|
City
|
1
|
Hansen
|
Ola
|
Timoteivn 10
|
Sandnes
|
2
|
Svendson
|
Tove
|
Borgvn 23
|
Sandnes
|
SQL Wildcards
SQL wildcards can substitute for one
or more characters when searching for data in a database.
SQL wildcards must be used with the
SQL LIKE operator.
With SQL, the following wildcards
can be used:
Wildcard
|
Description
|
%
|
A substitute for zero
or more characters
|
_
|
A substitute for
exactly one character
|
[charlist]
|
Any single character
in charlist
|
[^charlist]
or
[!charlist]
|
Any single character
not in charlist
|
SQL Wildcard Examples
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
|
Using the % Wildcard
Now we want to select the persons
living in a city that starts with "sa" from the "Persons"
table.
We use the following SELECT
statement:
SELECT * FROM Persons
WHERE City LIKE 'sa%'
WHERE City LIKE 'sa%'
The result-set will look like this:
P_Id
|
LastName
|
FirstName
|
Address
|
City
|
1
|
Hansen
|
Ola
|
Timoteivn 10
|
Sandnes
|
2
|
Svendson
|
Tove
|
Borgvn 23
|
Sandnes
|
Next, we want to select the persons
living in a city that contains the pattern "nes" from the
"Persons" table.
We use the following SELECT
statement:
SELECT * FROM Persons
WHERE City LIKE '%nes%'
WHERE City LIKE '%nes%'
The result-set will look like this:
P_Id
|
LastName
|
FirstName
|
Address
|
City
|
1
|
Hansen
|
Ola
|
Timoteivn 10
|
Sandnes
|
2
|
Svendson
|
Tove
|
Borgvn 23
|
Sandnes
|
Using the _ Wildcard
Now we want to select the persons
with a first name that starts with any character, followed by "la"
from the "Persons" table.
We use the following SELECT
statement:
SELECT * FROM Persons
WHERE FirstName LIKE '_la'
WHERE FirstName LIKE '_la'
The result-set will look like this:
P_Id
|
LastName
|
FirstName
|
Address
|
City
|
1
|
Hansen
|
Ola
|
Timoteivn 10
|
Sandnes
|
Next, we want to select the persons
with a last name that starts with "S", followed by any character,
followed by "end", followed by any character, followed by
"on" from the "Persons" table.
We use the following SELECT
statement:
SELECT * FROM Persons
WHERE LastName LIKE 'S_end_on'
WHERE LastName LIKE 'S_end_on'
The result-set will look like this:
P_Id
|
LastName
|
FirstName
|
Address
|
City
|
2
|
Svendson
|
Tove
|
Borgvn 23
|
Sandnes
|
Using the [charlist] Wildcard
Now we want to select the persons
with a last name that starts with "b" or "s" or
"p" from the "Persons" table.
We use the following SELECT
statement:
SELECT * FROM Persons
WHERE LastName LIKE '[bsp]%'
WHERE LastName LIKE '[bsp]%'
The result-set will look like this:
P_Id
|
LastName
|
FirstName
|
Address
|
City
|
2
|
Svendson
|
Tove
|
Borgvn 23
|
Sandnes
|
3
|
Pettersen
|
Kari
|
Storgt 20
|
Stavanger
|
Next, we want to select the persons
with a last name that do not start with "b" or "s" or
"p" from the "Persons" table.
We use the following SELECT
statement:
SELECT * FROM Persons
WHERE LastName LIKE '[!bsp]%'
WHERE LastName LIKE '[!bsp]%'
The result-set will look like this:
P_Id
|
LastName
|
FirstName
|
Address
|
City
|
1
|
Hansen
|
Ola
|
Timoteivn 10
|
Sandnes
|
The IN Operator
The IN operator allows you to
specify multiple values in a WHERE clause.
SQL IN Syntax
SELECT column_name(s)
FROM table_name
WHERE column_name IN (value1,value2,...)
FROM table_name
WHERE column_name IN (value1,value2,...)
IN SQL Operator Example
The "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 persons
with a last name equal to "Hansen" or "Pettersen" from the
table above.
We use the following SELECT
statement:
SELECT * FROM Persons
WHERE LastName IN ('Hansen','Pettersen')
WHERE LastName IN ('Hansen','Pettersen')
The result-set will look like this:
P_Id
|
LastName
|
FirstName
|
Address
|
City
|
1
|
Hansen
|
Ola
|
Timoteivn 10
|
Sandnes
|
3
|
Pettersen
|
Kari
|
Storgt 20
|
Stavanger
|
The SQL BETWEEN Operator
The BETWEEN operator selects a range
of data between two values. The values can be numbers, text, or dates.
SQL BETWEEN Syntax
SELECT column_name(s)
FROM table_name
WHERE column_name
BETWEEN value1 AND value2
FROM table_name
WHERE column_name
BETWEEN value1 AND value2
BETWEEN Operator Example
The "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 persons
with a last name alphabetically between "Hansen" and
"Pettersen" from the table above.
We use the following SELECT
statement:
SELECT * FROM Persons
WHERE LastName
BETWEEN 'Hansen' AND 'Pettersen'
WHERE LastName
BETWEEN 'Hansen' AND 'Pettersen'
The result-set will look like this:
P_Id
|
LastName
|
FirstName
|
Address
|
City
|
1
|
Hansen
|
Ola
|
Timoteivn 10
|
Sandnes
|
Note: The BETWEEN operator is treated differently in
different databases!
In some databases, persons with the
LastName of "Hansen" or "Pettersen" will not be listed,
because the BETWEEN operator only selects fields that are between and excluding
the test values.
In other databases, persons with the
LastName of "Hansen" or "Pettersen" will be listed, because
the BETWEEN operator selects fields that are between and including the test
values.
And in other databases, persons with
the LastName of "Hansen" will be listed, but "Pettersen"
will not be listed (like the example above), because the BETWEEN operator
selects fields between the test values, including the first test value and
excluding the last test value.
Therefore: Check how your database
treats the BETWEEN operator.
Example 2
To display the persons outside the
range in the previous example, use NOT BETWEEN:
SELECT * FROM Persons
WHERE LastName
NOT BETWEEN 'Hansen' AND 'Pettersen'
WHERE LastName
NOT BETWEEN 'Hansen' AND 'Pettersen'
The result-set will look like this:
P_Id
|
LastName
|
FirstName
|
Address
|
City
|
2
|
Svendson
|
Tove
|
Borgvn 23
|
Sandnes
|
3
|
Pettersen
|
Kari
|
Storgt 20
|
Stavanger
|
SQL Alias
You can give a table or a column
another name by using an alias. This can be a good thing to do if you have very
long or complex table names or column names.
An alias name could be anything, but
usually it is short.
SQL Alias Syntax for Tables
SELECT column_name(s)
FROM table_name
AS alias_name
FROM table_name
AS alias_name
SQL Alias Syntax for Columns
SELECT column_name AS alias_name
FROM table_name
FROM table_name
Alias Example
Assume we have a table called
"Persons" and another table called "Product_Orders". We
will give the table aliases of "p" and "po" respectively.
Now we want to list all the orders
that "Ola Hansen" is responsible for.
We use the following SELECT statement:
SELECT po.OrderID, p.LastName,
p.FirstName
FROM Persons AS p,
Product_Orders AS po
WHERE p.LastName='Hansen' AND p.FirstName='Ola'
FROM Persons AS p,
Product_Orders AS po
WHERE p.LastName='Hansen' AND p.FirstName='Ola'
The same SELECT statement without
aliases:
SELECT Product_Orders.OrderID,
Persons.LastName, Persons.FirstName
FROM Persons,
Product_Orders
WHERE Persons.LastName='Hansen' AND Persons.FirstName='Ola'
FROM Persons,
Product_Orders
WHERE Persons.LastName='Hansen' AND Persons.FirstName='Ola'
As you'll see from the two SELECT
statements above; aliases can make queries easier to both write and to read.
SQL JOIN
The JOIN keyword is used in an SQL
statement to query data from two or more tables, based on a relationship
between certain columns in these tables.
Tables in a database are often
related to each other with keys.
A primary key is a column (or a
combination of columns) with a unique value for each row. Each primary key
value must be unique within the table. The purpose is to bind data together,
across tables, without repeating all of the data in every table.
Look at the "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
|
Note that the "P_Id"
column is the primary key in the "Persons" table. This means
that no two rows can have the same P_Id. The P_Id
distinguishes two persons even if they have the same name.
Next, we have the "Orders"
table:
O_Id
|
OrderNo
|
P_Id
|
1
|
77895
|
3
|
2
|
44678
|
3
|
3
|
22456
|
1
|
4
|
24562
|
1
|
5
|
34764
|
15
|
Note that the "O_Id"
column is the primary key in the "Orders" table and that the
"P_Id" column refers to the persons in the "Persons" table
without using their names.
Notice that the relationship between
the two tables above is the "P_Id" column.
Different SQL JOINs
Before we continue with examples, we
will list the types of JOIN you can use, and the differences between them.
- JOIN: Return rows when there is at least one match in both tables
- LEFT JOIN: Return all rows from the left table, even if there are no matches in the right table
- RIGHT JOIN: Return all rows from the right table, even if there are no matches in the left table
- FULL JOIN: Return rows when there is a match in one of the tables
SQL INNER JOIN Keyword
The INNER JOIN keyword return rows
when there is at least one match in both tables.
SQL INNER JOIN Syntax
SELECT column_name(s)
FROM table_name1
INNER JOIN table_name2
ON table_name1.column_name=table_name2.column_name
FROM table_name1
INNER JOIN table_name2
ON table_name1.column_name=table_name2.column_name
PS: INNER JOIN is the same as JOIN.
SQL INNER JOIN Example
The "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
|
The "Orders" table:
O_Id
|
OrderNo
|
P_Id
|
1
|
77895
|
3
|
2
|
44678
|
3
|
3
|
22456
|
1
|
4
|
24562
|
1
|
5
|
34764
|
15
|
Now we want to list all the persons
with any orders.
We use the following SELECT
statement:
SELECT Persons.LastName,
Persons.FirstName, Orders.OrderNo
FROM Persons
INNER JOIN Orders
ON Persons.P_Id=Orders.P_Id
ORDER BY Persons.LastName
FROM Persons
INNER JOIN Orders
ON Persons.P_Id=Orders.P_Id
ORDER BY Persons.LastName
The result-set will look like this:
LastName
|
FirstName
|
OrderNo
|
Hansen
|
Ola
|
22456
|
Hansen
|
Ola
|
24562
|
Pettersen
|
Kari
|
77895
|
Pettersen
|
Kari
|
44678
|
The INNER JOIN keyword return rows
when there is at least one match in both tables. If there are rows in
"Persons" that do not have matches in "Orders", those rows
will NOT be listed.
SQL LEFT JOIN Keyword
The LEFT JOIN keyword returns all
rows from the left table (table_name1), even if there are no matches in the
right table (table_name2).
SQL LEFT JOIN Syntax
SELECT column_name(s)
FROM table_name1
LEFT JOIN table_name2
ON table_name1.column_name=table_name2.column_name
FROM table_name1
LEFT JOIN table_name2
ON table_name1.column_name=table_name2.column_name
PS: In some databases LEFT JOIN is called LEFT OUTER JOIN.
SQL LEFT JOIN Example
The "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
|
The "Orders" table:
O_Id
|
OrderNo
|
P_Id
|
1
|
77895
|
3
|
2
|
44678
|
3
|
3
|
22456
|
1
|
4
|
24562
|
1
|
5
|
34764
|
15
|
Now we want to list all the persons
and their orders - if any, from the tables above.
We use the following SELECT
statement:
SELECT Persons.LastName,
Persons.FirstName, Orders.OrderNo
FROM Persons
LEFT JOIN Orders
ON Persons.P_Id=Orders.P_Id
ORDER BY Persons.LastName
FROM Persons
LEFT JOIN Orders
ON Persons.P_Id=Orders.P_Id
ORDER BY Persons.LastName
The result-set will look like this:
LastName
|
FirstName
|
OrderNo
|
Hansen
|
Ola
|
22456
|
Hansen
|
Ola
|
24562
|
Pettersen
|
Kari
|
77895
|
Pettersen
|
Kari
|
44678
|
Svendson
|
Tove
|
The LEFT JOIN keyword returns all
the rows from the left table (Persons), even if there are no matches in the
right table (Orders).
SQL RIGHT JOIN Keyword
The RIGHT JOIN keyword returns all
the rows from the right table (table_name2), even if there are no matches in
the left table (table_name1).
SQL RIGHT JOIN Syntax
SELECT column_name(s)
FROM table_name1
RIGHT JOIN table_name2
ON table_name1.column_name=table_name2.column_name
FROM table_name1
RIGHT JOIN table_name2
ON table_name1.column_name=table_name2.column_name
PS: In some databases RIGHT JOIN is called RIGHT OUTER
JOIN.
SQL RIGHT JOIN Example
The "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
|
The "Orders" table:
O_Id
|
OrderNo
|
P_Id
|
1
|
77895
|
3
|
2
|
44678
|
3
|
3
|
22456
|
1
|
4
|
24562
|
1
|
5
|
34764
|
15
|
Now we want to list all the orders
with containing persons - if any, from the tables above.
We use the following SELECT
statement:
SELECT Persons.LastName,
Persons.FirstName, Orders.OrderNo
FROM Persons
RIGHT JOIN Orders
ON Persons.P_Id=Orders.P_Id
ORDER BY Persons.LastName
FROM Persons
RIGHT JOIN Orders
ON Persons.P_Id=Orders.P_Id
ORDER BY Persons.LastName
The result-set will look like this:
LastName
|
FirstName
|
OrderNo
|
Hansen
|
Ola
|
22456
|
Hansen
|
Ola
|
24562
|
Pettersen
|
Kari
|
77895
|
Pettersen
|
Kari
|
44678
|
34764
|
The RIGHT JOIN keyword returns all
the rows from the right table (Orders), even if there are no matches in the
left table (Persons).
SQL FULL JOIN Keyword
The FULL JOIN keyword return rows
when there is a match in one of the tables.
SQL FULL JOIN Syntax
SELECT column_name(s)
FROM table_name1
FULL JOIN table_name2
ON table_name1.column_name=table_name2.column_name
FROM table_name1
FULL JOIN table_name2
ON table_name1.column_name=table_name2.column_name
SQL FULL JOIN Example
The "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
|
The "Orders" table:
O_Id
|
OrderNo
|
P_Id
|
1
|
77895
|
3
|
2
|
44678
|
3
|
3
|
22456
|
1
|
4
|
24562
|
1
|
5
|
34764
|
15
|
Now we want to list all the persons
and their orders, and all the orders with their persons.
We use the following SELECT
statement:
SELECT Persons.LastName,
Persons.FirstName, Orders.OrderNo
FROM Persons
FULL JOIN Orders
ON Persons.P_Id=Orders.P_Id
ORDER BY Persons.LastName
FROM Persons
FULL JOIN Orders
ON Persons.P_Id=Orders.P_Id
ORDER BY Persons.LastName
The result-set will look like this:
LastName
|
FirstName
|
OrderNo
|
Hansen
|
Ola
|
22456
|
Hansen
|
Ola
|
24562
|
Pettersen
|
Kari
|
77895
|
Pettersen
|
Kari
|
44678
|
Svendson
|
Tove
|
|
34764
|
The FULL JOIN keyword returns all
the rows from the left table (Persons), and all the rows from the right table
(Orders). If there are rows in "Persons" that do not have matches in
"Orders", or if there are rows in "Orders" that do not have
matches in "Persons", those rows will be listed as well.
The SQL UNION Operator
The UNION operator is used to
combine the result-set of two or more SELECT statements.
Notice that each SELECT statement
within the UNION must have the same number of columns. The columns must also
have similar data types. Also, the columns in each SELECT statement must be in
the same order.
SQL UNION Syntax
SELECT column_name(s) FROM
table_name1
UNION
SELECT column_name(s) FROM table_name2
UNION
SELECT column_name(s) FROM table_name2
Note: The UNION operator selects only distinct values by
default. To allow duplicate values, use UNION ALL.
SQL UNION ALL Syntax
SELECT column_name(s) FROM
table_name1
UNION ALL
SELECT column_name(s) FROM table_name2
UNION ALL
SELECT column_name(s) FROM table_name2
PS: The column names in the result-set of a UNION are
always equal to the column names in the first SELECT statement in the UNION.
SQL UNION Example
Look at the following tables:
"Employees_Norway":
E_ID
|
E_Name
|
01
|
Hansen, Ola
|
02
|
Svendson, Tove
|
03
|
Svendson, Stephen
|
04
|
Pettersen, Kari
|
"Employees_USA":
E_ID
|
E_Name
|
01
|
Turner, Sally
|
02
|
Kent, Clark
|
03
|
Svendson, Stephen
|
04
|
Scott, Stephen
|
Now we want to list all the
different employees in Norway and USA.
We use the following SELECT
statement:
SELECT E_Name FROM Employees_Norway
UNION
SELECT E_Name FROM Employees_USA
UNION
SELECT E_Name FROM Employees_USA
The result-set will look like this:
E_Name
|
Hansen, Ola
|
Svendson, Tove
|
Svendson, Stephen
|
Pettersen, Kari
|
Turner, Sally
|
Kent, Clark
|
Scott, Stephen
|
Note: This command cannot be used to list all employees in
Norway and USA. In the example above we have two employees with equal names,
and only one of them will be listed. The UNION command selects only distinct
values.
SQL UNION ALL Example
Now we want to list all employees
in Norway and USA:
SELECT E_Name FROM Employees_Norway
UNION ALL
SELECT E_Name FROM Employees_USA
UNION ALL
SELECT E_Name FROM Employees_USA
Result
E_Name
|
Hansen, Ola
|
Svendson, Tove
|
Svendson, Stephen
|
Pettersen, Kari
|
Turner, Sally
|
Kent, Clark
|
Svendson, Stephen
|
Scott, Stephen
|
The SQL SELECT INTO Statement
The SELECT INTO statement selects
data from one table and inserts it into a different table.
The SELECT INTO statement is most
often used to create backup copies of tables.
SQL SELECT INTO Syntax
We can select all columns into the
new table:
SELECT *
INTO new_table_name [IN externaldatabase]
FROM old_tablename
INTO new_table_name [IN externaldatabase]
FROM old_tablename
Or we can select only the columns we
want into the new table:
SELECT column_name(s)
INTO new_table_name [IN externaldatabase]
FROM old_tablename
INTO new_table_name [IN externaldatabase]
FROM old_tablename
SQL SELECT INTO Example
Make a Backup Copy - Now we want to make an exact copy of the data in our
"Persons" table.
We use the following SQL statement:
SELECT *
INTO Persons_Backup
FROM Persons
INTO Persons_Backup
FROM Persons
We can also use the IN clause to
copy the table into another database:
SELECT *
INTO Persons_Backup IN 'Backup.mdb'
FROM Persons
INTO Persons_Backup IN 'Backup.mdb'
FROM Persons
We can also copy only a few fields
into the new table:
SELECT LastName,FirstName
INTO Persons_Backup
FROM Persons
INTO Persons_Backup
FROM Persons
SQL SELECT INTO - With a WHERE
Clause
We can also add a WHERE clause.
The following SQL statement creates
a "Persons_Backup" table with only the persons who lives in the city
"Sandnes":
SELECT LastName,Firstname
INTO Persons_Backup
FROM Persons
WHERE City='Sandnes'
INTO Persons_Backup
FROM Persons
WHERE City='Sandnes'
SQL SELECT INTO - Joined Tables
Selecting data from more than one
table is also possible.
The following example creates a
"Persons_Order_Backup" table contains data from the two tables
"Persons" and "Orders":
SELECT
Persons.LastName,Orders.OrderNo
INTO Persons_Order_Backup
FROM Persons
INNER JOIN Orders
ON Persons.P_Id=Orders.P_Id
INTO Persons_Order_Backup
FROM Persons
INNER JOIN Orders
ON Persons.P_Id=Orders.P_Id
The CREATE DATABASE Statement
The CREATE DATABASE statement is
used to create a database.
SQL CREATE DATABASE Syntax
CREATE DATABASE database_name
CREATE DATABASE Example
Now we want to create a database
called "my_db".
We use the following CREATE DATABASE
statement:
CREATE DATABASE my_db
Database tables can be added with
the CREATE TABLE statement.
The CREATE TABLE Statement
The CREATE TABLE statement is used
to create a table in a database.
SQL CREATE TABLE Syntax
CREATE TABLE table_name
(
column_name1 data_type,
column_name2 data_type,
column_name3 data_type,
....
)
(
column_name1 data_type,
column_name2 data_type,
column_name3 data_type,
....
)
The data type specifies what type of
data the column can hold. For a complete reference of all the data types
available in MS Access, MySQL, and SQL Server, go to our complete Data
Types reference.
CREATE TABLE Example
Now we want to create a table called
"Persons" that contains five columns: P_Id, LastName, FirstName,
Address, and City.
We use the following CREATE TABLE
statement:
CREATE TABLE Persons
(
P_Id int,
LastName varchar(255),
FirstName varchar(255),
Address varchar(255),
City varchar(255)
)
(
P_Id int,
LastName varchar(255),
FirstName varchar(255),
Address varchar(255),
City varchar(255)
)
The P_Id column is of type int and
will hold a number. The LastName, FirstName, Address, and City columns are of
type varchar with a maximum length of 255 characters.
The empty "Persons" table
will now look like this:
P_Id
|
LastName
|
FirstName
|
Address
|
City
|
The empty table can be filled with
data with the INSERT INTO statement.
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