Learn SQL

SQL is a standard language for accessing databases.

Our SQL tutorial will teach you how to use SQL to access and manipulate data in:

MySQL, SQL Server, Access, Oracle, Sybase, DB2, and other database systems.

Introduction to SQL

SQL is a standard language for accessing and manipulating databases.

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What is SQL?

• SQL stands for Structured Query Language
• SQL lets you access and manipulate databases
• SQL is an ANSI (American National Standards Institute) standard

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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

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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!

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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

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RDBMS

RDBMS stands for Relational Database Management System.
RDBMS is the basis for SQL, and for all modern database systems like 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 collections 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).

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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.

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Keep in Mind That...

• SQL is not case sensitive

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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.

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SQL DML and DDL

SQL can be divided into two parts: The Data Manipulation Language (DML) and the Data Definition Language (DDL).
The query and update commands form the DML part of SQL:

• SELECT - extracts data from a database
• UPDATE - updates data in a database
• DELETE - deletes data from a database
• INSERT INTO - inserts new data into a database

The DDL part of SQL permits database tables to be created or deleted. It also define indexes (keys), specify links between tables, and impose constraints between tables. The most important DDL statements in SQL are:

• CREATE DATABASE - creates a new database
• ALTER DATABASE - modifies a database
• CREATE TABLE - creates a new table
• ALTER TABLE - modifies a table
• DROP TABLE - deletes a table
• CREATE INDEX - creates an index (search key)
• DROP INDEX - deletes an index 

SQL SELECT Statement

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.

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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

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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

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SQL SELECT DISTINCT Statement

This chapter will explain the SELECT DISTINCT statement.

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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

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SELECT DISTINCT Example

The "Persons" table:

P_Id	LastName	FirstName	Address	City
1	Hansen	Ola	Timoteivn 10	Sandnes
2	Svendson	Tove	Borgvn 23	Sandnes
3	Pettersen	Kari	Storgt 20	Stavanger

Now we want to select only the distinct values from the column named "City" from the table above.
We use the following SELECT statement:

SELECT DISTINCT City FROM Persons

The result-set will look like this:

City
Sandnes
Stavanger

 

The WHERE clause is used to filter records.

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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

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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

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Quotes Around Text Fields

SQL uses single quotes around text values (most database systems will also accept double quotes).
Although, 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'

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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	If you know the exact value you want to return for at least one of the columns

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.

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The AND & OR Operators

The AND operator displays a record if both the first condition and the second condition is true.
The OR operator displays a record if either the first condition or the second condition is true.

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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

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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

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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.

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The ORDER BY Keyword

The ORDER BY keyword is used to sort the result-set by a specified column.
The ORDER BY keyword sort the records in ascending order by default.
If you want to sort the records in a descending order, you can use the DESC keyword.

SQL ORDER BY Syntax

SELECT column_name(s) FROM table_name ORDER BY column_name(s) ASC|DESC

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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

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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.

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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,...)

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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

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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.

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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!

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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

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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.

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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!

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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

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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 Try It

Test your SQL Skills

On this page you can test your SQL skills.
We will use the Customers table in the Northwind database:

CompanyName	ContactName	Address	City
Alfreds Futterkiste	Maria Anders	Obere Str. 57	Berlin
Berglunds snabbköp	Christina Berglund	Berguvsvägen 8	Luleå
Centro comercial Moctezuma	Francisco Chang	Sierras de Granada 9993	México D.F.
Ernst Handel	Roland Mendel	Kirchgasse 6	Graz
FISSA Fabrica Inter. Salchichas S.A.	Diego Roel	C/ Moralzarzal, 86	Madrid
Galería del gastrónomo	Eduardo Saavedra	Rambla de Cataluña, 23	Barcelona
Island Trading	Helen Bennett	Garden House Crowther Way	Cowes
Königlich Essen	Philip Cramer	Maubelstr. 90	Brandenburg
Laughing Bacchus Wine Cellars	Yoshi Tannamuri	1900 Oak St.	Vancouver
Magazzini Alimentari Riuniti	Giovanni Rovelli	Via Ludovico il Moro 22	Bergamo
North/South	Simon Crowther	South House 300 Queensbridge	London
Paris spécialités	Marie Bertrand	265, boulevard Charonne	Paris
Rattlesnake Canyon Grocery	Paula Wilson	2817 Milton Dr.	Albuquerque
Simons bistro	Jytte Petersen	Vinbæltet 34	København
The Big Cheese	Liz Nixon	89 Jefferson Way Suite 2	Portland
Vaffeljernet	Palle Ibsen	Smagsløget 45	Århus
Wolski Zajazd	Zbyszek Piestrzeniewicz	ul. Filtrowa 68	Warszawa

To preserve space, the table above is a subset of the Customers table used in the example below.

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Try it Yourself

To see how SQL works, you can copy the SQL statements below and paste them into the textarea, or you can make your own SQL statements.

SELECT * FROM customers

SELECT CompanyName, ContactName FROM customers

SELECT * FROM customers WHERE companyname LIKE 'a%'

SELECT CompanyName, ContactName FROM customers WHERE CompanyName > 'a'

 When using SQL on text data, "alfred" is greater than "a" (like in a dictionary).

SELECT CompanyName, ContactName FROM customers WHERE CompanyName > 'g' AND ContactName > 'g'

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

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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

Oracle Syntax

SELECT column_name(s) FROM table_name WHERE ROWNUM <= number

Example

SELECT * FROM Persons WHERE ROWNUM <=5

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SQL TOP Example

The "Persons" table:

P_Id	LastName	FirstName	Address	City
1	Hansen	Ola	Timoteivn 10	Sandnes
2	Svendson	Tove	Borgvn 23	Sandnes
3	Pettersen	Kari	Storgt 20	Stavanger
4	Nilsen	Tom	Vingvn 23	Stavanger

Now we want to select only the two first records in the table above.
We use the following SELECT statement:

SELECT TOP 2 * FROM Persons

The result-set will look like this:

P_Id	LastName	FirstName	Address	City
1	Hansen	Ola	Timoteivn 10	Sandnes
2	Svendson	Tove	Borgvn 23	Sandnes

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SQL TOP PERCENT Example

The "Persons" table:

P_Id	LastName	FirstName	Address	City
1	Hansen	Ola	Timoteivn 10	Sandnes
2	Svendson	Tove	Borgvn 23	Sandnes
3	Pettersen	Kari	Storgt 20	Stavanger
4	Nilsen	Tom	Vingvn 23	Stavanger

Now we want to select only 50% of the records in the table above.
We use the following SELECT statement:

SELECT TOP 50 PERCENT * FROM Persons

The result-set will look like this:

P_Id	LastName	FirstName	Address	City
1	Hansen	Ola	Timoteivn 10	Sandnes
2	Svendson	Tove	Borgvn 23	Sandnes

SQL LIKE Operator

The LIKE operator is used in a WHERE clause to search for a specified pattern in a column.

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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

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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 NOT contains 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.

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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

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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

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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

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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

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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,...)

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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.

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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

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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.

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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.

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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

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Alias Example

Assume we have a table called "Persons" and another table called "Product_Orders". We will give the table aliases of "p" an "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 to both 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.

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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.

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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 return rows when there is at least one match in both tables.

SQL INNER JOIN Syntax

SELECT column_name(s) FROM table_name1 INNER JOIN table_name2 ON table_name1.column_name=table_name2.column_name

PS: INNER JOIN is the same as JOIN.

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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 return rows when there is at least one match in both tables. If there are rows in "Persons" that do not have matches in "Orders", those rows will NOT be listed.

SQL LEFT JOIN Keyword

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.

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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

SQL RIGHT JOIN Keyword

The RIGHT JOIN keyword Return all 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.

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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

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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.

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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.

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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.

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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

he SQL SELECT INTO statement can be used to create backup copies of tables.

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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

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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

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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'

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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

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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.

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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 details.

SQL NOT NULL Constraint

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.

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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) )

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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)

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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