-->
Introduction to SQL
SQL is a standard language for accessing and manipulating
databases.
What is SQL?
What Can SQL do?
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 is a Standard - BUT....
Although SQL is an ANSI (American National Standards Institute)
standard, there are many different versions of the SQL language.
However, to be compliant with the ANSI standard, they all support
at least the major commands (such as SELECT, UPDATE, DELETE, INSERT,
WHERE) in a similar manner.
Note: Most of the SQL database programs also have their own
proprietary extensions in addition to the SQL standard!
Using SQL in Your Web Site
To build a web site that shows some data from a database, you will
need the following:
An RDBMS database program (i.e. MS
Access, SQL Server, MySQL)
A server-side scripting language,
like PHP or ASP
SQL
- HTML / CSS
RDBMS
RDBMS stands for Relational Database Management System.
RDBMS is the basis for SQL, and for all modern database systems
such as MS SQL Server, IBM DB2, Oracle, MySQL, and Microsoft Access.
The data in RDBMS is stored in database objects called tables.
A table is a collection of related data entries and it consists of
columns and rows.
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.
What is DDL, DML and DCL?
Data Definition Language deals with database schemas and
descriptions of how the data should reside in the database, therefore
language statements like CREATE TABLE or ALTER TABLE belong to DDL.
DML deals with data manipulation, and therefore includes most common
SQL statements such SELECT, INSERT, etc. Data Control Language
includes commands such as GRANT, and mostly concerns with rights,
permissions and other controls of the database system.
DDL
Data Definition Language (DDL) statements are used to define the
database structure or schema.
CREATE - to create objects in the
database
ALTER - alters the structure of
the database
DROP - delete objects from the
database
TRUNCATE - remove all records from
a table, including all spaces allocated for the records are removed
COMMENT - add comments to the data
dictionary
- RENAME - rename an object
DML
Data Manipulation Language (DML) statements are used for managing
data within schema objects.
SELECT - retrieve data from the a
database
INSERT - insert data into a table
UPDATE - updates existing data
within a table
DELETE - deletes all records from
a table, the space for the records remain
MERGE - UPSERT operation (insert
or update)
CALL - call a PL/SQL or Java
subprogram
EXPLAIN PLAN - explain access path
to data
- LOCK TABLE - control concurrency
DCL
Data Control Language (DCL) statements.
SQL SELECT Statement
This chapter will explain the SELECT and the SELECT * statements.
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
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 |
SQL SELECT DISTINCT Statement
This chapter will explain the SELECT DISTINCT statement.
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
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:
SQL WHERE Clause
The WHERE clause is used to filter records.
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
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'
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
For numeric values:
This is correct:
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 !=
SQL AND & OR Operators
The AND & OR operators are used to filter records based on
more than one condition.
The AND & OR Operators
The AND operator displays a record if both the first condition and
the second condition are 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'
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'
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')
The result-set will look like this:
P_Id
|
LastName
|
FirstName
|
Address
|
City
|
| 2 |
Svendson |
Tove |
Borgvn 23 |
Sandnes |
SQL ORDER BY Keyword
The ORDER BY keyword is used to sort the result-set.
The ORDER BY Keyword
The ORDER BY keyword is used to sort the result-set by a specified
column.
The ORDER BY keyword sorts 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
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
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
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 |
SQL INSERT INTO Statement
The INSERT INTO statement is used to insert new records in a
table.
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,...)
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,...)
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')
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')
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 |
|
|
SQL UPDATE Statement
The UPDATE statement is used to update records in a table.
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
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'
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'
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 |
SQL DELETE Statement
The DELETE statement is used to delete records in a table.
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
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'
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
Note: Be very careful when deleting records. You cannot
undo this statement!
SQL TOP Clause
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
SQL SELECT TOP Equivalent in MySQL and Oracle
MySQL Syntax
SELECT column_name(s)
FROM table_name
LIMIT number
Example
SELECT *
FROM Persons
LIMIT 5
SQL LIKE Operator
The LIKE operator is used in a WHERE clause to search for a
specified pattern in a column.
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
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%'
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'
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%'
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%'
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 be used when searching for data in a database.
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%'
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%'
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'
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'
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]%'
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]%'
The result-set will look like this:
P_Id
|
LastName
|
FirstName
|
Address
|
City
|
| 1 |
Hansen |
Ola |
Timoteivn 10 |
Sandnes |
SQL IN Operator
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,...)
IN 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')
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 |
SQL BETWEEN Operator
The BETWEEN operator is used in a WHERE clause to select a range
of data between two values.
The 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
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'
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'
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
With SQL, an alias name can be given to a table or to a column.
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
SQL Alias Syntax for Columns
SELECT column_name AS alias_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'
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'
As you'll see from the two SELECT statements above; aliases can
make queries easier both to write and to read.
SQL Joins
SQL joins are used to query data from two or more tables, based on
a relationship between certain columns in these tables.
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
SQL INNER JOIN Keyword
The INNER JOIN keyword returns 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
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
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 returns 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
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
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
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
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
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
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
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
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.
SQL UNION Operator
The SQL UNION operator combines two or more SELECT statements.
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
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
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
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
Result
E_Name
|
| Hansen, Ola |
| Svendson, Tove |
| Svendson, Stephen |
| Pettersen, Kari |
| Turner, Sally |
| Kent, Clark |
| Svendson, Stephen |
| Scott, Stephen |
SQL SELECT INTO Statement
The SQL SELECT INTO statement can be used to create backup copies
of tables.
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
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
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
We can also use the IN clause to copy the table into another
database:
SELECT *
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
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'
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
SQL CREATE DATABASE Statement
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.
SQL 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,
....
)
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)
)
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.
SQL Constraints
SQL Constraints
Constraints are used to limit the type of data that can go into a
table.
Constraints can be specified when a table is created (with the
CREATE TABLE statement) or after the table is created (with the ALTER
TABLE statement).
We will focus on the following constraints:
NOT NULL
UNIQUE
PRIMARY KEY
FOREIGN KEY
CHECK
- DEFAULT
The next chapters will describe each constraint in detail.
SQL NOT NULL Constraint
By default, a table column can hold NULL values.
SQL NOT NULL Constraint
The NOT NULL constraint enforces a column to NOT accept NULL
values.
The NOT NULL constraint enforces a field to always contain a
value. This means that you cannot insert a new record, or update a
record without adding a value to this field.
The following SQL enforces the "P_Id" column and the
"LastName" column to not accept NULL values:
CREATE TABLE Persons
(
P_Id int
NOT NULL,
LastName varchar(255) NOT NULL,
FirstName
varchar(255),
Address varchar(255),
City varchar(255)
)
SQL UNIQUE Constraint
SQL UNIQUE Constraint
The UNIQUE constraint uniquely identifies each record in a
database table.
The UNIQUE and PRIMARY KEY constraints both provide a guarantee
for uniqueness for a column or set of columns.
A PRIMARY KEY constraint automatically has a UNIQUE constraint
defined on it.
Note that you can have many UNIQUE constraints per table, but only
one PRIMARY KEY constraint per table.
SQL UNIQUE Constraint on CREATE TABLE
The following SQL creates a UNIQUE constraint on the "P_Id"
column when the "Persons" table is created:
MySQL:
CREATE TABLE Persons
(
P_Id int NOT NULL,
LastName
varchar(255) NOT NULL,
FirstName varchar(255),
Address
varchar(255),
City varchar(255),
UNIQUE (P_Id)
)
SQL Server / Oracle / MS Access:
CREATE TABLE Persons
(
P_Id int NOT NULL UNIQUE,
LastName
varchar(255) NOT NULL,
FirstName varchar(255),
Address
varchar(255),
City varchar(255)
)
To allow naming of a UNIQUE constraint, and for defining a UNIQUE
constraint on multiple columns, use the following SQL syntax:
MySQL / SQL Server / Oracle / MS Access:
CREATE TABLE Persons
(
P_Id int
NOT NULL,
LastName varchar(255) NOT NULL,
FirstName
varchar(255),
Address varchar(255),
City
varchar(255),
CONSTRAINT uc_PersonID UNIQUE (P_Id,LastName)
)
SQL UNIQUE Constraint on ALTER TABLE
To create a UNIQUE constraint on the "P_Id" column when
the table is already created, use the following SQL:
MySQL / SQL Server / Oracle / MS Access:
ALTER TABLE Persons
ADD UNIQUE (P_Id)
To allow naming of a UNIQUE constraint, and for defining a UNIQUE
constraint on multiple columns, use the following SQL syntax:
MySQL / SQL Server / Oracle / MS Access:
ALTER TABLE Persons
ADD CONSTRAINT
uc_PersonID UNIQUE (P_Id,LastName)
To DROP a UNIQUE Constraint
To drop a UNIQUE constraint, use the following SQL:
MySQL:
ALTER TABLE Persons
DROP INDEX uc_PersonID
SQL Server / Oracle / MS Access:
ALTER TABLE Persons
DROP CONSTRAINT
uc_PersonID
SQL PRIMARY KEY Constraint
SQL PRIMARY KEY Constraint
The PRIMARY KEY constraint uniquely identifies each record in a
database table.
Primary keys must contain unique values.
A primary key column cannot contain NULL values.
Each table should have a primary key, and each table can have only
ONE primary key.
SQL PRIMARY KEY Constraint on CREATE TABLE
The following SQL creates a PRIMARY KEY on the "P_Id"
column when the "Persons" table is created:
MySQL:
CREATE TABLE Persons
(
P_Id int NOT NULL,
LastName
varchar(255) NOT NULL,
FirstName varchar(255),
Address
varchar(255),
City varchar(255),
PRIMARY KEY (P_Id)
)
SQL Server / Oracle / MS Access:
CREATE TABLE Persons
(
P_Id int NOT NULL PRIMARY
KEY,
LastName varchar(255) NOT NULL,
FirstName
varchar(255),
Address varchar(255),
City varchar(255)
)
To allow naming of a PRIMARY KEY constraint, and for defining a
PRIMARY KEY constraint on multiple columns, use the following SQL
syntax:
MySQL / SQL Server / Oracle / MS Access:
CREATE TABLE Persons
(
P_Id int NOT NULL,
LastName
varchar(255) NOT NULL,
FirstName varchar(255),
Address
varchar(255),
City varchar(255),
CONSTRAINT pk_PersonID PRIMARY
KEY (P_Id,LastName)
)
Note: In the example above there is only ONE PRIMARY KEY
(pk_PersonID). However, the value of the pk_PersonID is made up of
two columns (P_Id and LastName).
SQL PRIMARY KEY Constraint on ALTER TABLE
To create a PRIMARY KEY constraint on the "P_Id" column
when the table is already created, use the following SQL:
MySQL / SQL Server / Oracle / MS Access:
ALTER TABLE Persons
ADD PRIMARY KEY (P_Id)
To allow naming of a PRIMARY KEY constraint, and for defining a
PRIMARY KEY constraint on multiple columns, use the following SQL
syntax:
MySQL / SQL Server / Oracle / MS Access:
ALTER TABLE Persons
ADD CONSTRAINT pk_PersonID PRIMARY KEY
(P_Id,LastName)
Note: If you use the ALTER TABLE statement to add a primary
key, the primary key column(s) must already have been declared to not
contain NULL values (when the table was first created).
To DROP a PRIMARY KEY Constraint
To drop a PRIMARY KEY constraint, use the following SQL:
MySQL:
ALTER TABLE Persons
DROP PRIMARY KEY
SQL Server / Oracle / MS Access:
ALTER TABLE Persons
DROP CONSTRAINT
pk_PersonID
SQL FOREIGN KEY Constraint
A FOREIGN KEY in one table points to a PRIMARY KEY in another
table.
Let's illustrate the foreign key with an example. Look at the
following two tables:
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 |
2 |
| 4 |
24562 |
1 |
Note that the "P_Id" column in the "Orders"
table points to the "P_Id" column in the "Persons"
table.
The "P_Id" column in the "Persons" table is
the PRIMARY KEY in the "Persons" table.
The "P_Id" column in the "Orders" table is a
FOREIGN KEY in the "Orders" table.
The FOREIGN KEY constraint is used to prevent actions that would
destroy links between tables.
The FOREIGN KEY constraint also prevents that invalid data form
being inserted into the foreign key column, because it has to be one
of the values contained in the table it points to.
SQL FOREIGN KEY Constraint on CREATE TABLE
The following SQL creates a FOREIGN KEY on the "P_Id"
column when the "Orders" table is created:
MySQL:
CREATE TABLE Orders
(
O_Id int NOT NULL,
OrderNo int NOT
NULL,
P_Id int,
PRIMARY KEY (O_Id),
FOREIGN KEY (P_Id)
REFERENCES Persons(P_Id)
)
SQL Server / Oracle / MS Access:
CREATE TABLE Orders
(
O_Id int NOT NULL PRIMARY KEY,
OrderNo
int NOT NULL,
P_Id int FOREIGN KEY REFERENCES Persons(P_Id)
)
To allow naming of a FOREIGN KEY constraint, and for defining a
FOREIGN KEY constraint on multiple columns, use the following SQL
syntax:
MySQL / SQL Server / Oracle / MS Access:
CREATE TABLE Orders
(
O_Id int
NOT NULL,
OrderNo int NOT NULL,
P_Id int,
PRIMARY KEY
(O_Id),
CONSTRAINT fk_PerOrders FOREIGN KEY (P_Id)
REFERENCES
Persons(P_Id)
)
SQL FOREIGN KEY Constraint on ALTER TABLE
To create a FOREIGN KEY constraint on the "P_Id" column
when the "Orders" table is already created, use the
following SQL:
MySQL / SQL Server / Oracle / MS Access:
ALTER TABLE Orders
ADD FOREIGN KEY (P_Id)
REFERENCES
Persons(P_Id)
To allow naming of a FOREIGN KEY constraint, and for defining a
FOREIGN KEY constraint on multiple columns, use the following SQL
syntax:
MySQL / SQL Server / Oracle / MS Access:
ALTER TABLE Orders
ADD CONSTRAINT
fk_PerOrders
FOREIGN KEY (P_Id)
REFERENCES Persons(P_Id)
To DROP a FOREIGN KEY Constraint
To drop a FOREIGN KEY constraint, use the following SQL:
MySQL:
ALTER TABLE Orders
DROP FOREIGN KEY fk_PerOrders
SQL Server / Oracle / MS Access:
ALTER TABLE Orders
DROP CONSTRAINT
fk_PerOrders
SQL CHECK Constraint
The CHECK constraint is used to limit the value range that can be
placed in a column.
If you define a CHECK constraint on a single column it allows only
certain values for this column.
If you define a CHECK constraint on a table it can limit the
values in certain columns based on values in other columns in the
row.
SQL CHECK Constraint on CREATE TABLE
The following SQL creates a CHECK constraint on the "P_Id"
column when the "Persons" table is created. The CHECK
constraint specifies that the column "P_Id" must only
include integers greater than 0.
MySQL:
CREATE TABLE Persons
(
P_Id int NOT NULL,
LastName
varchar(255) NOT NULL,
FirstName varchar(255),
Address
varchar(255),
City varchar(255),
CHECK (P_Id>0)
)
SQL Server / Oracle / MS Access:
CREATE TABLE Persons
(
P_Id int NOT NULL CHECK
(P_Id>0),
LastName varchar(255) NOT NULL,
FirstName
varchar(255),
Address varchar(255),
City varchar(255)
)
To allow naming of a CHECK constraint, and for defining a CHECK
constraint on multiple columns, use the following SQL syntax:
MySQL / SQL Server / Oracle / MS Access:
CREATE TABLE Persons
(
P_Id int
NOT NULL,
LastName varchar(255) NOT NULL,
FirstName
varchar(255),
Address varchar(255),
City
varchar(255),
CONSTRAINT chk_Person CHECK (P_Id>0 AND
City='Sandnes')
)
SQL CHECK Constraint on ALTER TABLE
To create a CHECK constraint on the "P_Id" column when
the table is already created, use the following SQL:
MySQL / SQL Server / Oracle / MS Access:
ALTER TABLE Persons
ADD CHECK (P_Id>0)
To allow naming of a CHECK constraint, and for defining a CHECK
constraint on multiple columns, use the following SQL syntax:
MySQL / SQL Server / Oracle / MS Access:
ALTER TABLE Persons
ADD CONSTRAINT
chk_Person CHECK (P_Id>0 AND City='Sandnes')
To DROP a CHECK Constraint
To drop a CHECK constraint, use the following SQL:
SQL Server / Oracle / MS Access:
ALTER TABLE Persons
DROP CONSTRAINT chk_Person
MySQL:
ALTER TABLE Persons
DROP CHECK
chk_Person
SQL DEFAULT Constraint
The DEFAULT constraint is used to insert a default value into a
column.
The default value will be added to all new records, if no other
value is specified.
SQL DEFAULT Constraint on CREATE TABLE
The following SQL creates a DEFAULT constraint on the "City"
column when the "Persons" table is created:
My SQL / SQL Server / Oracle / MS Access:
CREATE TABLE Persons
(
P_Id int NOT NULL,
LastName
varchar(255) NOT NULL,
FirstName varchar(255),
Address
varchar(255),
City varchar(255) DEFAULT 'Sandnes'
)
The DEFAULT constraint can also be used to insert system values,
by using functions like GETDATE():
CREATE TABLE Orders
(
O_Id int
NOT NULL,
OrderNo int NOT NULL,
P_Id int,
OrderDate date
DEFAULT GETDATE()
)
SQL DEFAULT Constraint on ALTER TABLE
To create a DEFAULT constraint on the "City" column when
the table is already created, use the following SQL:
MySQL:
ALTER TABLE Persons
ALTER City SET DEFAULT 'SANDNES'
SQL Server / MS Access:
ALTER TABLE Persons
ALTER COLUMN City SET DEFAULT 'SANDNES'
Oracle:
ALTER TABLE Persons
MODIFY City
DEFAULT 'SANDNES'
To DROP a DEFAULT Constraint
To drop a DEFAULT constraint, use the following SQL:
MySQL:
ALTER TABLE Persons
ALTER City DROP DEFAULT
SQL Server / Oracle / MS Access:
ALTER TABLE Persons
ALTER COLUMN
City DROP DEFAULT
SQL CREATE INDEX Statement
The CREATE INDEX statement is used to create indexes in tables.
Indexes allow the database application to find data fast; without
reading the whole table.
Indexes
An index can be created in a table to find data more quickly and
efficiently.
The users cannot see the indexes, they are just used to speed up
searches/queries.
Note: Updating a table with indexes takes more time than
updating a table without (because the indexes also need an update).
So you should only create indexes on columns (and tables) that will
be frequently searched against.
SQL CREATE INDEX Syntax
Creates an index on a table. Duplicate values are allowed:
CREATE INDEX index_name
ON table_name (column_name)
SQL CREATE UNIQUE INDEX Syntax
Creates a unique index on a table. Duplicate values are not
allowed:
CREATE UNIQUE INDEX index_name
ON table_name (column_name)
Note: The syntax for creating indexes varies amongst
different databases. Therefore: Check the syntax for creating indexes
in your database.
CREATE INDEX Example
The SQL statement below creates an index named "PIndex"
on the "LastName" column in the "Persons" table:
CREATE INDEX PIndex
ON Persons (LastName)
If you want to create an index on a combination of columns, you
can list the column names within the parentheses, separated by
commas:
CREATE INDEX PIndex
ON Persons
(LastName, FirstName)
SQL DROP INDEX, DROP TABLE, and DROP DATABASE
The DROP INDEX Statement
The DROP INDEX statement is used to delete an index in a table.
DROP INDEX Syntax for MS Access:
DROP INDEX index_name ON table_name
DROP INDEX Syntax for MS SQL Server:
DROP INDEX table_name.index_name
DROP INDEX Syntax for DB2/Oracle:
DROP INDEX index_name
DROP INDEX Syntax for MySQL:
ALTER TABLE table_name DROP INDEX
index_name
The DROP TABLE Statement
The DROP TABLE statement is used to delete a table.
DROP TABLE table_name
The DROP DATABASE Statement
The DROP DATABASE statement is used to delete a database.
DROP DATABASE database_name
The TRUNCATE TABLE Statement
What if we only want to delete the data inside the table, and not
the table itself?
Then, use the TRUNCATE TABLE statement:
TRUNCATE TABLE table_name
SQL ALTER TABLE Statement
The ALTER TABLE Statement
The ALTER TABLE statement is used to add, delete, or modify
columns in an existing table.
SQL ALTER TABLE Syntax
To add a column in a table, use the following syntax:
ALTER TABLE table_name
ADD column_name datatype
To delete a column in a table, use the following syntax (notice
that some database systems don't allow deleting a column):
ALTER TABLE table_name
DROP COLUMN column_name
To change the data type of a column in a table, use the following
syntax:
SQL Server / MS Access:
ALTER TABLE table_name
ALTER COLUMN column_name datatype
My SQL / Oracle:
ALTER TABLE table_name
MODIFY
column_name datatype
SQL ALTER TABLE Example
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 |
Now we want to add a column named "DateOfBirth" in the
"Persons" table.
We use the following SQL statement:
ALTER TABLE Persons
ADD DateOfBirth date
Notice that the new column, "DateOfBirth", is of type
date and is going to hold a date. 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.
The "Persons" table will now like this:
P_Id
|
LastName
|
FirstName
|
Address
|
City
|
DateOfBirth
|
| 1 |
Hansen |
Ola |
Timoteivn 10 |
Sandnes |
|
| 2 |
Svendson |
Tove |
Borgvn 23 |
Sandnes |
|
| 3 |
Pettersen |
Kari |
Storgt 20 |
Stavanger |
|
Change Data Type Example
Now we want to change the data type of the column named
"DateOfBirth" in the "Persons" table.
We use the following SQL statement:
ALTER TABLE Persons
ALTER COLUMN DateOfBirth year
Notice that the "DateOfBirth" column is now of type year
and is going to hold a year in a two-digit or four-digit format.
DROP COLUMN Example
Next, we want to delete the column named "DateOfBirth"
in the "Persons" table.
We use the following SQL statement:
ALTER TABLE Persons
DROP COLUMN DateOfBirth
The "Persons" table will now 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 |
SQL AUTO INCREMENT Field
Auto-increment allows a unique number to be generated when a new
record is inserted into a table.
AUTO INCREMENT a Field
Very often we would like the value of the primary key field to be
created automatically every time a new record is inserted.
We would like to create an auto-increment field in a table.
Syntax for MySQL
The following SQL statement defines the "P_Id" column to
be an auto-increment primary key field in the "Persons"
table:
CREATE TABLE Persons
(
P_Id int NOT NULL
AUTO_INCREMENT,
LastName varchar(255) NOT NULL,
FirstName
varchar(255),
Address varchar(255),
City varchar(255),
PRIMARY
KEY (P_Id)
)
MySQL uses the AUTO_INCREMENT keyword to perform an auto-increment
feature.
By default, the starting value for AUTO_INCREMENT is 1, and it
will increment by 1 for each new record.
To let the AUTO_INCREMENT sequence start with another value, use
the following SQL statement:
ALTER TABLE Persons AUTO_INCREMENT=100
To insert a new record into the "Persons" table, we will
not have to specify a value for the "P_Id" column (a unique
value will be added automatically):
INSERT INTO Persons (FirstName,LastName)
VALUES
('Lars','Monsen')
The SQL statement above would insert a new record into the
"Persons" table. The "P_Id" column would be
assigned a unique value. The "FirstName" column would be
set to "Lars" and the "LastName" column would be
set to "Monsen".
Syntax for SQL Server
The following SQL statement defines the "P_Id" column to
be an auto-increment primary key field in the "Persons"
table:
CREATE TABLE Persons
(
P_Id int PRIMARY KEY
IDENTITY,
LastName varchar(255) NOT NULL,
FirstName
varchar(255),
Address varchar(255),
City varchar(255)
)
The MS SQL Server uses the IDENTITY keyword to perform an
auto-increment feature.
By default, the starting value for IDENTITY is 1, and it will
increment by 1 for each new record.
To specify that the "P_Id" column should start at value
10 and increment by 5, change the identity to IDENTITY(10,5).
To insert a new record into the "Persons" table, we will
not have to specify a value for the "P_Id" column (a unique
value will be added automatically):
INSERT INTO Persons (FirstName,LastName)
VALUES
('Lars','Monsen')
The SQL statement above would insert a new record into the
"Persons" table. The "P_Id" column would be
assigned a unique value. The "FirstName" column would be
set to "Lars" and the "LastName" column would be
set to "Monsen".
Syntax for Access
The following SQL statement defines the "P_Id" column to
be an auto-increment primary key field in the "Persons"
table:
CREATE TABLE Persons
(
P_Id PRIMARY KEY
AUTOINCREMENT,
LastName varchar(255) NOT NULL,
FirstName
varchar(255),
Address varchar(255),
City varchar(255)
)
The MS Access uses the AUTOINCREMENT keyword to perform an
auto-increment feature.
By default, the starting value for AUTOINCREMENT is 1, and it will
increment by 1 for each new record.
To specify that the "P_Id" column should start at value
10 and increment by 5, change the autoincrement to
AUTOINCREMENT(10,5).
To insert a new record into the "Persons" table, we will
not have to specify a value for the "P_Id" column (a unique
value will be added automatically):
INSERT INTO Persons (FirstName,LastName)
VALUES
('Lars','Monsen')
The SQL statement above would insert a new record into the
"Persons" table. The "P_Id" column would be
assigned a unique value. The "FirstName" column would be
set to "Lars" and the "LastName" column would be
set to "Monsen".
Syntax for Oracle
In Oracle the code is a little bit more tricky.
You will have to create an auto-increment field with the sequence
object (this object generates a number sequence).
Use the following CREATE SEQUENCE syntax:
CREATE SEQUENCE seq_person
MINVALUE 1
START WITH 1
INCREMENT
BY 1
CACHE 10
The code above creates a sequence object called seq_person, that
starts with 1 and will increment by 1. It will also cache up to 10
values for performance. The cache option specifies how many sequence
values will be stored in memory for faster access.
To insert a new record into the "Persons" table, we will
have to use the nextval function (this function retrieves the next
value from seq_person sequence):
INSERT INTO Persons (P_Id,FirstName,LastName)
VALUES
(seq_person.nextval,'Lars','Monsen')
The SQL statement above would insert a new record into the
"Persons" table. The "P_Id" column would be
assigned the next number from the seq_person sequence. The
"FirstName" column would be set to "Lars" and the
"LastName" column would be set to "Monsen".
SQL Views
A view is a virtual table.
This chapter shows how to create, update, and delete a view.
SQL CREATE VIEW Statement
In SQL, a view is a virtual table based on the result-set of an
SQL statement.
A view contains rows and columns, just like a real table. The
fields in a view are fields from one or more real tables in the
database.
You can add SQL functions, WHERE, and JOIN statements to a view
and present the data as if the data were coming from one single
table.
SQL CREATE VIEW Syntax
CREATE VIEW view_name AS
SELECT column_name(s)
FROM
table_name
WHERE condition
Note: A view always shows up-to-date data! The database
engine recreates the data, using the view's SQL statement, every time
a user queries a view.
SQL CREATE VIEW Examples
If you have the Northwind database you can see that it has several
views installed by default.
The view "Current Product List" lists all active
products (products that are not discontinued) from the "Products"
table. The view is created with the following SQL:
CREATE VIEW [Current Product List] AS
SELECT
ProductID,ProductName
FROM Products
WHERE Discontinued=No
We can query the view above as follows:
SELECT * FROM [Current Product List]
Another view in the Northwind sample database selects every
product in the "Products" table with a unit price higher
than the average unit price:
CREATE VIEW [Products Above Average Price] AS
SELECT
ProductName,UnitPrice
FROM Products
WHERE UnitPrice>(SELECT
AVG(UnitPrice) FROM Products)
We can query the view above as follows:
SELECT * FROM [Products Above Average Price]
Another view in the Northwind database calculates the total sale
for each category in 1997. Note that this view selects its data from
another view called "Product Sales for 1997":
CREATE VIEW [Category Sales For 1997] AS
SELECT DISTINCT
CategoryName,Sum(ProductSales) AS CategorySales
FROM [Product
Sales for 1997]
GROUP BY CategoryName
We can query the view above as follows:
SELECT * FROM [Category Sales For 1997]
We can also add a condition to the query. Now we want to see the
total sale only for the category "Beverages":
SELECT * FROM [Category Sales For
1997]
WHERE CategoryName='Beverages'
SQL Updating a View
You can update a view by using the following syntax:
SQL CREATE OR REPLACE VIEW Syntax
CREATE OR REPLACE VIEW view_name AS
SELECT column_name(s)
FROM
table_name
WHERE condition
Now we want to add the "Category" column to the "Current
Product List" view. We will update the view with the following
SQL:
CREATE VIEW [Current Product List]
AS
SELECT ProductID,ProductName,Category
FROM Products
WHERE
Discontinued=No
SQL Dropping a View
You can delete a view with the DROP VIEW command.
SQL DROP VIEW Syntax
DROP VIEW view_name
SQL Date Functions
SQL Dates
The most difficult part when working with dates is to be sure that
the format of the date you are trying to insert, matches the format
of the date column in the database.
As long as your data contains only the date portion, your queries
will work as expected. However, if a time portion is involved, it
gets complicated.
Before talking about the complications of querying for dates, we
will look at the most important built-in functions for working with
dates.
MySQL Date Functions
The following table lists the most important built-in date
functions in MySQL:
Function
|
Description
|
| NOW() |
Returns the current date and time |
| CURDATE() |
Returns the current date |
| CURTIME() |
Returns the current time |
| DATE() |
Extracts the date part of a date or date/time expression |
| EXTRACT() |
Returns a single part of a date/time |
| DATE_ADD() |
Adds a specified time interval to a date |
| DATE_SUB() |
Subtracts a specified time interval from a date |
| DATEDIFF() |
Returns the number of days between two dates |
| DATE_FORMAT() |
Displays date/time data in different formats |
SQL Server Date Functions
The following table lists the most important built-in date
functions in SQL Server:
Function
|
Description
|
| GETDATE() |
Returns the current date and time |
| DATEPART() |
Returns a single part of a date/time |
| DATEADD() |
Adds or subtracts a specified time interval from a date |
| DATEDIFF() |
Returns the time between two dates |
| CONVERT() |
Displays date/time data in different formats |
SQL Date Data Types
MySQL comes with the following data types for storing a
date or a date/time value in the database:
SQL Server comes with the following data types for storing
a date or a date/time value in the database:
Note: The date types are chosen for a column when you
create a new table in your database!
For an overview of all data types available, go to our complete
Data Types
reference.
SQL Working with Dates
You can compare two dates easily if there is no time component
involved!
Assume we have the following "Orders" table:
OrderId
|
ProductName
|
OrderDate
|
| 1 |
Geitost |
2008-11-11 |
| 2 |
Camembert Pierrot |
2008-11-09 |
| 3 |
Mozzarella di Giovanni |
2008-11-11 |
| 4 |
Mascarpone Fabioli |
2008-10-29 |
Now we want to select the records with an OrderDate of
"2008-11-11" from the table above.
We use the following SELECT statement:
SELECT * FROM Orders WHERE OrderDate='2008-11-11'
The result-set will look like this:
OrderId
|
ProductName
|
OrderDate
|
| 1 |
Geitost |
2008-11-11 |
| 3 |
Mozzarella di Giovanni |
2008-11-11 |
Now, assume that the "Orders" table looks like this
(notice the time component in the "OrderDate" column):
OrderId
|
ProductName
|
OrderDate
|
| 1 |
Geitost |
2008-11-11 13:23:44 |
| 2 |
Camembert Pierrot |
2008-11-09 15:45:21 |
| 3 |
Mozzarella di Giovanni |
2008-11-11 11:12:01 |
| 4 |
Mascarpone Fabioli |
2008-10-29 14:56:59 |
If we use the same SELECT statement as above:
SELECT * FROM Orders WHERE OrderDate='2008-11-11'
we will get no result! This is because the query is looking only
for dates with no time portion.
Tip: If you want to keep your queries simple and easy to
maintain, do not allow time components in your dates!
SQL NULL Values
NULL values represent missing unknown data.
By default, a table column can hold NULL values.
This chapter will explain the IS NULL and IS NOT NULL operators.
SQL NULL Values
If a column in a table is optional, we can insert a new record or
update an existing record without adding a value to this column. This
means that the field will be saved with a NULL value.
NULL values are treated differently from other values.
NULL is used as a placeholder for unknown or inapplicable values.
Note: It is not possible to compare NULL and 0; they are not
equivalent.
SQL Working with NULL Values
Look at the following "Persons" table:
P_Id
|
LastName
|
FirstName
|
Address
|
City
|
| 1 |
Hansen |
Ola |
|
Sandnes |
| 2 |
Svendson |
Tove |
Borgvn 23 |
Sandnes |
| 3 |
Pettersen |
Kari |
|
Stavanger |
Suppose that the "Address" column in the "Persons"
table is optional. This means that if we insert a record with no
value for the "Address" column, the "Address"
column will be saved with a NULL value.
How can we test for NULL values?
It is not possible to test for NULL values with comparison
operators, such as =, <, or <>.
We will have to use the IS NULL and IS NOT NULL operators instead.
SQL IS NULL
How do we select only the records with NULL values in the
"Address" column?
We will have to use the IS NULL operator:
SELECT LastName,FirstName,Address FROM Persons
WHERE Address IS
NULL
The result-set will look like this:
LastName
|
FirstName
|
Address
|
| Hansen |
Ola |
|
| Pettersen |
Kari |
|
Tip: Always use IS NULL to look for NULL values.
SQL IS NOT NULL
How do we select only the records with no NULL values in the
"Address" column?
We will have to use the IS NOT NULL operator:
SELECT LastName,FirstName,Address FROM Persons
WHERE Address IS
NOT NULL
The result-set will look like this:
LastName
|
FirstName
|
Address
|
| Svendson |
Tove |
Borgvn 23 |
In the next chapter we will look at the ISNULL(), NVL(), IFNULL()
and COALESCE() functions.
SQL NULL Functions
SQL ISNULL(), NVL(), IFNULL() and COALESCE()
Functions
Look at the following "Products" table:
P_Id
|
ProductName
|
UnitPrice
|
UnitsInStock
|
UnitsOnOrder
|
| 1 |
Jarlsberg |
10.45 |
16 |
15 |
| 2 |
Mascarpone |
32.56 |
23 |
|
| 3 |
Gorgonzola |
15.67 |
9 |
20 |
Suppose that the "UnitsOnOrder" column is optional, and
may contain NULL values.
We have the following SELECT statement:
SELECT ProductName,UnitPrice*(UnitsInStock+UnitsOnOrder)
FROM
Products
In the example above, if any of the "UnitsOnOrder"
values are NULL, the result is NULL.
Microsoft's ISNULL() function is used to specify how we want to
treat NULL values.
The NVL(), IFNULL(), and COALESCE() functions can also be used to
achieve the same result.
In this case we want NULL values to be zero.
Below, if "UnitsOnOrder" is NULL it will not harm the
calculation, because ISNULL() returns a zero if the value is NULL:
SQL Server / MS Access
SELECT
ProductName,UnitPrice*(UnitsInStock+ISNULL(UnitsOnOrder,0))
FROM
Products
Oracle
Oracle does not have an ISNULL() function. However, we can use the
NVL() function to achieve the same result:
SELECT
ProductName,UnitPrice*(UnitsInStock+NVL(UnitsOnOrder,0))
FROM
Products
MySQL
MySQL does have an ISNULL() function. However, it works a little
bit different from Microsoft's ISNULL() function.
In MySQL we can use the IFNULL() function, like this:
SELECT
ProductName,UnitPrice*(UnitsInStock+IFNULL(UnitsOnOrder,0))
FROM
Products
or we can use the COALESCE() function, like this:
SELECT
ProductName,UnitPrice*(UnitsInStock+COALESCE(UnitsOnOrder,0))
FROM
Products
SQL Data Types
MySQL Data Types
In MySQL there are three main types : text, number, and Date/Time
types.
Text types:
Data type
|
Description
|
CHAR(size)
|
Holds a fixed length string (can contain letters,
numbers, and special characters). The fixed size is specified in
parenthesis. Can store up to 255 characters
|
VARCHAR(size)
|
Holds a variable length string (can contain letters,
numbers, and special characters). The maximum size is specified in
parenthesis. Can store up to 255 characters. Note: If you
put a greater value than 255 it will be converted to a TEXT type
|
TINYTEXT
|
Holds a string with a maximum length of 255
characters
|
TEXT
|
Holds a string with a maximum length of 65,535
characters
|
BLOB
|
For BLOBs (Binary Large OBjects). Holds up to 65,535
bytes of data
|
MEDIUMTEXT
|
Holds a string with a maximum length of 16,777,215
characters
|
MEDIUMBLOB
|
For BLOBs (Binary Large OBjects). Holds up to
16,777,215 bytes of data
|
LONGTEXT
|
Holds a string with a maximum length of
4,294,967,295 characters
|
LONGBLOB
|
For BLOBs (Binary Large OBjects). Holds up to
4,294,967,295 bytes of data
|
ENUM(x,y,z,etc.)
|
Let you enter a list of
possible values. You can list up to 65535 values in an ENUM list.
If a value is inserted that is not in the list, a blank value will
be inserted.
Note: The values
are sorted in the order you enter them.
You enter the possible values in this format:
ENUM('X','Y','Z')
|
SET
|
Similar to ENUM except that SET may contain up to 64
list items and can store more than one choice
|
Number types:
Data type
|
Description
|
TINYINT(size)
|
-128 to 127 normal. 0 to 255 UNSIGNED*. The maximum
number of digits may be specified in parenthesis
|
SMALLINT(size)
|
-32768 to 32767 normal. 0 to 65535 UNSIGNED*. The
maximum number of digits may be specified in parenthesis
|
MEDIUMINT(size)
|
-8388608 to 8388607 normal. 0 to 16777215 UNSIGNED*.
The maximum number of digits may be specified in parenthesis
|
INT(size)
|
-2147483648 to 2147483647 normal. 0 to 4294967295
UNSIGNED*. The maximum number of digits may be specified in
parenthesis
|
BIGINT(size)
|
-9223372036854775808 to 9223372036854775807 normal.
0 to 18446744073709551615 UNSIGNED*. The maximum number of digits
may be specified in parenthesis
|
FLOAT(size,d)
|
A small number with a floating decimal point. The
maximum number of digits may be specified in the size parameter.
The maximum number of digits to the right of the decimal point is
specified in the d parameter
|
DOUBLE(size,d)
|
A large number with a floating decimal point. The
maximum number of digits may be specified in the size parameter.
The maximum number of digits to the right of the decimal point is
specified in the d parameter
|
DECIMAL(size,d)
|
A DOUBLE stored as a string , allowing for a fixed
decimal point. The maximum number of digits may be specified in
the size parameter. The maximum number of digits to the right of
the decimal point is specified in the d parameter
|
*The integer types have an extra option called UNSIGNED. Normally,
the integer goes from an negative to positive value. Adding the
UNSIGNED attribute will move that range up so it starts at zero
instead of a negative number.
Date types:
Data type
|
Description
|
DATE()
|
A date. Format:
YYYY-MM-DD
Note: The supported range is from
'1000-01-01' to '9999-12-31'
|
DATETIME()
|
*A date and time
combination. Format: YYYY-MM-DD HH:MM:SS
Note: The supported range is from '1000-01-01
00:00:00' to '9999-12-31 23:59:59'
|
TIMESTAMP()
|
*A timestamp. TIMESTAMP
values are stored as the number of seconds since the Unix epoch
('1970-01-01 00:00:00' UTC). Format: YYYY-MM-DD HH:MM:SS
Note: The supported range is from '1970-01-01
00:00:01' UTC to '2038-01-09 03:14:07' UTC
|
TIME()
|
A time. Format:
HH:MM:SS
Note: The supported range is from
'-838:59:59' to '838:59:59'
|
YEAR()
|
A year in two-digit or
four-digit format.
Note: Values allowed in four-digit format:
1901 to 2155. Values allowed in two-digit format: 70 to 69,
representing years from 1970 to 2069
|
*Even if DATETIME and TIMESTAMP return the same format, they work
very differently. In an INSERT or UPDATE query, the TIMESTAMP
automatically set itself to the current date and time. TIMESTAMP also
accepts various formats, like YYYYMMDDHHMMSS, YYMMDDHHMMSS, YYYYMMDD,
or YYMMDD.
SQL Functions
SQL has many built-in functions for performing calculations on
data.
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.
SQL AVG() Function
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:
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 |
SQL COUNT() Function
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:
SQL COUNT(*) Example
If we omit the WHERE clause, like this:
SELECT COUNT(*) AS NumberOfOrders FROM Orders
The result-set will look like this:
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:
which is the number of unique customers (Hansen, Nilsen, and
Jensen) in the "Orders" table.
SQL FIRST() Function
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:
SQL LAST() Function
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:
SQL MAX() Function
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:
SQL MIN() Function
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:
SQL SUM() Function
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:
SQL GROUP BY Statement
Aggregate functions often need an added GROUP BY statement.
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
SQL HAVING Clause
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 |
SQL UCASE() Function
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 |
SQL LCASE() Function
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 |
SQL MID() Function
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:
SQL LEN() Function
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:
SQL ROUND() Function
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 |
SQL NOW() Function
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 |
SQL FORMAT() Function
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 |
SQL Quick Reference From W3Schools
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
|
