What SQL[1]

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What is SQL

SQL is short for Structured Query Language and is a widely used database language, providing means of datamanipulation (store, retrieve, update, delete) and database creation.

Almost all modern Relational Database Management Systems like MS SQL Server, Microsoft Access, MSDE,Oracle, DB2, Sybase, MySQL, Postgres and Informix use SQL as standard database language. Now a word of

warning here, although all those RDBMS use SQL, they use different SQL dialects. For example MS SQL Serverspecific version of the SQL is called T-SQL, Oracle version of SQL is called PL/SQL, MS Access version of SQL is

called JET SQL, etc.

Our SQL tutorial will teach you how to use commonly used SQL commands and you will be able to apply most

of the knowledge gathered from this SQL tutorial to any of the databases above.

Table Creation in SQL

The foundation of every Relational Database Management System is a database object called table. Every

database consists of one or more tables, which store the database’s data/information. Each table has its own

unique name and consists of columns and rows.

The database table columns (called also table fields) have their own unique names and have a pre-defined datatypes. Table columns can have various attributes defining the column functionality (the column is a primary

key, there is an index defined on the column, the column has certain default value, etc.).

While table columns describe the data types, the table rows contain the actual data for the columns.

Here is an example of a simple database table, containing customers data. The first row, listed in bold, contains

the names of the table columns:

Table: Customers

FirstName LastName Email DOB Phone

John Smith [email protected] 2/4/1968 626 222-2222

Steven Goldfish [email protected] 4/4/1974 323 455-4545

Paula Brown [email protected] 5/24/1978 416 323-3232

James Smith [email protected] 20/10/1980 416 323-8888

Now that we’ve learned what is a database table, we can continue with our sql tutorial and learn how to

manipulate the data within the database tables.

Select Command

The SQL SELECT statement is used to select data from a SQL database table. This is usually the very first SQL

command every SQL newbie learns and this is because the SELECT SQL statement is one of the most used SQL

commands.

Please have a look at the general SQL SELECT syntax:

SELECT Column1, Column2, Column3,

FROM Table1

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The list of column names after the SQL SELECT command determines which columns you want to be returned

in your result set. If you want to select all columns from a database table, you can use the following SQL

statement:

SELECT *

FROM Table1

When the list of columns following the SELECT SQL command is replaced with asterix (*) all table columns are

returned. Word of caution here, it’s always better to explicitly specify the columns in the SELECT list, as this will

improve your query performance significantly.

The table name following the SQL FROM keyword (in our case Table1) tells the SQL interpreter which table to

use to retrieve the data.

Select Into Command

The SQL SELECT INTO statement is used to select data from a SQL database table and to insert it to a

different table at the same time.

The general SQL SELECT INTO syntax looks like this:

SELECT Column1, Column2, Column3,

INTO Table2FROM Table1

The list of column names after the SQL SELECT command determines which columns will be copied, and the

table name after the SQL INTO keyword specifies to which table to copy those rows.

If we want to make an exact copy of the data in our Customers table, we need the following SQL SELECT

INTO statement:

SELECT *

INTO Customers_copy

FROM Customers

Select Distinct Command

The SQL DISTINCT clause is used together with the SQL SELECT keyword, to return a dataset with unique

entries for certain database table column.

We will use our Customers database table to illustrate the usage of SQL DISTINCT.



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For example if we want to select all distinct surnames from our Customers table, we will use the following SQL

DISTINCT statement:

SELECT DISTINCT LastName

FROM Customers

The result of the SQL DISTINCT expression above will look like this:

LastName

Smith

Goldfish

Brown

Where Command

The SQL WHERE clause is used to select data conditionally, by adding it to already existing SQL SELECT query.

We are going to use the Customers table from the previous chapter, to illustrate the use of the SQL WHERE

command.

Table: Customers






If we want to select all customers from our database table, having last name 'Smith' we need to use the

following SQL syntax:

SELECT *

FROM Customers

WHERE LastName = 'Smith'

The result of the SQL expression above will be the following:




In this simple SQL query we used the "=" (Equal) operator in our WHERE criteria:

LastName = 'Smith'

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But we can use any of the following comparison operators in conjunction with the SQL WHERE clause:

<> (Not Equal)

SELECT *

FROM Customers

WHERE LastName <> 'Smith'

> (Greater than)

SELECT *

FROM Customers

WHERE DOB > '1/1/1970'

>= (Greater or Equal)

SELECT *

FROM Customers

WHERE DOB >= '1/1/1970'

< (Less than)

SELECT *

FROM Customers

WHERE DOB < '1/1/1970'

<= (Less or Equal)

SELECT *FROM Customers

WHERE DOB =< '1/1/1970'

LIKE (similar to)

SELECT *

FROM Customers

WHERE Phone LIKE '626%'

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Note the LIKE syntax is different with the different RDBMS (SQL Server syntax used above). Check the SQL

LIKE article for more details.

Between (Defines a range)

SELECT *

FROM CustomersWHERE DOB BETWEEN '1/1/1970' AND '1/1/1975'

LIKE Command

We will use the Customers table to illustrate the SQL LIKE clause usage:






The SQL LIKE clause is very useful when you want to specify a search condition within your SQL WHERE

clause, based on a part of a column contents. For example if you want to select all customers having FirstName

starting with 'J' you need to use the following SQL statement:

SELECT *

FROM Customers

WHERE FirstName LIKE 'J%'

Here is the result of the SQL statement above:




If you want to select all Customers with phone numbers starting with '416' you will use this SQL expression:

SELECT *

FROM Customers

WHERE Phone LIKE '416%'

The '%' is a so called wildcard character and represents any string in our pattern.

You can put the wildcard anywhere in the string following the SQL LIKE clause and you can put as many

wildcards as you like too.

Note that different databases use different characters as wildcard characters, for example '%' is a wildcard

character for MS SQL Server representing any string, and '*' is the corresponding wildcard character used in MS

Access.

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Another wildcard character is '_' representing any single character.

The '[]' specifies a range of characters. Have a look at the following SQL statement:

SELECT *

FROM Customers

WHERE Phone LIKE '[4-6]_6%'

This SQL expression will return all customers satisfying the following conditions:

• The Phone column starts with a digit between 4 and 6 ([4-6])

• Second character in the Phone column can be anything (_)

• The third character in the Phone column is 6 (6)

• The remainder of the Phone column can be any character string (%)

Here is the result of this SQL expression:





INSERT INTO Command

The SQL INSERT INTO syntax has 2 main forms and the result of either of them is adding a new row into the

database table.

The first syntax form of the INSERT INTO SQL clause doesn't specify the column names where the data will be

inserted, but just their values:

INSERT INTO Table1

VALUES (value1, value2, value3…)

The second form of the SQL INSERT INTO command, specifies both the columns and the values to be insertedin them:

INSERT INTO Table1 (Column1, Column2, Column3…)

VALUES (Value1, Value2, Value3…)

As you might already have guessed, the number of the columns in the second INSERT INTO syntax form must

match the number of values into the SQL statement, otherwise you will get an error.

If we want to insert a new row into our Customers table, we are going to use one of the following 2 SQL

statements:

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INSERT INTO Customers

VALUES ('Peter', 'Hunt', '[email protected]', '1/1/1974', '626 888-8888')

INSERT INTO Customers (FirstName, LastName, Email, DOB, Phone)

VALUES ('Peter', 'Hunt', '[email protected]', '1/1/1974', '626 888-8888')

The result of the execution of either of the 2 INSERT INTO SQL statements will be a new row added to our

Customers database table:






Peter Hunt [email protected] 1/1/1974 626 888-8888

If you want to enter data for just a few of the table columns, you’ll have to use the second syntax form of the

SQL INSERT INTO clause, because the first form will produce an error if you haven’t supplied values for all

columns.

To insert only the FirstName and LastName columns, execute the following SQL statement:

INSERT INTO Customers (FirstName, LastName)

VALUES ('Peter', 'Hunt')

UPDATE Command

The SQL UPDATE general syntax looks like this:

UPDATE Table1

SET Column1 = Value1, Column2 = Value2

WHERE Some_Column = Some_Value

The SQL UPDATE clause changes the data in already existing database row(s) and usually we need to add a

conditional SQL WHERE clause to our SQL UPDATE statement in order to specify which row(s) we intend to

update.

If we want to update the Mr. Steven Goldfish's date of birth to '5/10/1974' in our Customers database table





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we need the following SQL UPDATE statement:

UPDATE Customers

SET DOB = '5/10/1974'

WHERE LastName = 'Goldfish' AND FirstName = 'Steven'

If we don’t specify a WHERE clause in the SQL expression above, all customers' DOB will be updated to

'5/10/1974', so be careful with the SQL UPDATE command usage.

We can update several database table rows at once, by using the SQL WHERE clause in our UPDATE statement.

For example if we want to change the phone number for all customers with last name Smith (we have 2 in our

example Customers table), we need to use the following SQL UPDATE statement:

UPDATE Customers

SET Phone = '626 555-5555'


After the execution of the UPDATE SQL expression above, the Customers table will look as follows:



Steven Goldfish [email protected] 4/4/1974 323 455-4545Paula Brown [email protected] 5/24/1978 416 323-3232


DELETE Command

So far we’ve learnt how to select data from a database table and how to insert and update data into a database

table. Now it’s time to learn how to remove data from a database. Here comes the SQL DELETE statement!

The SQL DELETE command has the following generic SQL syntax:

DELETE FROM Table1

WHERE Some_Column = Some_Value

If you skip the SQL WHERE clause when executing SQL DELETE expression, then all the data in the specified

table will be deleted. The following SQL statement will delete all the data from our Customers table and we’ll

end up with completely empty table:

DELETE FROM Table1

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If you specify a WHERE clause in your SQL DELETE statement, only the table rows satisfying the WHERE

criteria will be deleted:

DELETE FROM Customers


The SQL query above will delete all database rows having LastName 'Smith' and will leave the Customers table

in the following state:




ORDER BY Command

The SQL ORDER BY clause comes in handy when you want to sort your SQL result sets by some column(s).For example if you want to select all the persons from the already familiar Customers table and order the result

by date of birth, you will use the following statement:

SELECT * FROM Customers

ORDER BY DOB

The result of the above SQL expression will be the following:






As you can see the rows are sorted in ascending order by the DOB column, but what if you want to sort them in

descending order? To do that you will have to add the DESC SQL keyword after your SQL ORDER BY clause:


ORDER BY DOB DESC

The result of the SQL query above will look like this:






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If you don't specify how to order your rows, alphabetically or reverse, than the result set is ordered

alphabetically, hence the following to SQL expressions produce the same result:


ORDER BY DOB

SELECT * FROM CustomersORDER BY DOB ASC

You can sort your result set by more than one column by specifying those columns in the SQL ORDER BY list.

The following SQL expression will order by DOB and LastName:


ORDER BY DOB, LastName

OR & AND Command

The SQL AND clause is used when you want to specify more than one condition in your SQL WHERE clause,

and at the same time you want all conditions to be true.

For example if you want to select all customers with FirstName "John" and LastName "Smith", you will use the

following SQL expression:

SELECT * FROM CustomersWHERE FirstName = 'John' AND LastName = 'Smith'

The result of the SQL query above is:



The following row in our Customer table, satisfies the second of the conditions (LastName = 'Smith'), but not

the first one (FirstName = 'John'), and that's why it's not returned by our SQL query:



The SQL OR statement is used in similar fashion and the major difference compared to the SQL AND is that OR

clause will return all rows satisfying any of the conditions listed in the WHERE clause.

If we want to select all customers having FirstName 'James' or FirstName 'Paula' we need to use the following

SQL statement:


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WHERE FirstName = 'James' OR FirstName = 'Paula'

The result of this query will be the following:




You can combine AND and OR clauses anyway you want and you can use parentheses to define your logical

expressions.

Here is an example of such a SQL query, selecting all customers with LastName 'Brown' and FirstName either

'James' or 'Paula':


WHERE (FirstName = 'James' OR FirstName = 'Paula') AND LastName = 'Brown'

The result of the SQL expression above will be:



IN Command

The SQL IN clause allows you to specify discrete values in your SQL WHERE search criteria.

THE SQL IN syntax looks like this:

SELECT Column1, Column2, Column3, …

FROM Table1

WHERE Column1 IN (Valu1, Value2, …)

Lets use the EmployeeHours table to illustrate how SQL IN works:

Employee Date Hours

John Smith 5/6/2004 8

Allan Babel 5/6/2004 8

Tina Crown 5/6/2004 8







Consider the following SQL query using the SQL IN clause:

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SELECT *

FROM EmployeeHours

WHERE Date IN ('5/6/2004', '5/7/2004')

This SQL expression will select only the entries where the column Date has value of '5/6/2004' or '5/7/2004',

and you can see the result below:

Employee Date Hours







We can use the SQL IN statement with another column in our EmployeeHours table:

SELECT *

FROM EmployeeHours

WHERE Hours IN (9, 10)

The result of the SQL query above will be:

Employee Date Hours




BETWEEN Command

The SQL BETWEEN & AND keywords define a range of data between 2 values.

The SQL BETWEEN syntax looks like this:

SELECT Column1, Column2, Column3, …

FROM Table1

WHERE Column1 BETWEEN Value1 AND Value2

The 2 values defining the range for SQL BETWEEN clause can be dates, numbers or just text.

In contrast with the SQL IN keyword, which allows you to specify discrete values in your SQL WHERE criteria,

the SQL BETWEEN gives you the ability to specify a range in your search criteria.

We are going to use the familiar Customers table to show how SQL BETWEEN works:

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Consider the following SQL BETWEEN statement:

SELECT *

FROM Customers

WHERE DOB BETWEEN '1/1/1975' AND '1/1/2004'

The SQL BETWEEN statement above will select all Customers having DOB column between '1/1/1975' and

'1/1/2004' dates. Here is the result of this SQL expression:




ALIASES Command

SQL aliases can be used with database tables and with database table columns, depending on task you are

performing.

SQL column aliases are used to make the output of your SQL queries easy to read and more meaningful:

SELECT Employee, SUM(Hours) As SumHoursPerEmployee

FROM EmployeeHours

GROUP BY Employee

In the example above we created SQL alias SumHoursPerEmployee and the result of this SQL query will be the

following:

Employee SumHoursPerEmployee

John Smith 25

Allan Babel 24

Tina Crown 27

Consider the following SQL statement, showing how to use SQL table aliases:

SELECT Emp.Employee

FROM EmployeeHours AS Emp

Here is the result of the SQL expression above:

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Employee

John Smith

Allan Babel

Tina Crown

The SQL table aliases are very useful when you select data from multiple tables.

COUNT Command

The SQL COUNT aggregate function is used to count the number of rows in a database table.

The SQL COUNT syntax is simple and looks like this:

SELECT COUNT(Column1)

FROM Table1

If we want to count the number of customers in our Customers table, we will use the following SQL COUNT

statement:

SELECT COUNT(LastName) AS NumberOfCustomers

FROM Customers

The result of this SQL COUNT query will be:

NumberOfCustomers

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MAX Command

The SQL MAX aggregate function allows us to select the highest (maximum) value for a certain column.

The SQL MAX function syntax is very simple and it looks like this:

SELECT MAX(Column1)

FROM Table1

If we use the Customers table from our previous chapters, we can select the highest date of birth with the

following SQL MAX expression:

SELECT MAX(DOB) AS MaxDOB

FROM Customers

MIN Command

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The SQL MIN aggregate function allows us to select the lowest (minimum) value for a certain column.

The SQL MIN function syntax is very simple and it looks like this:

SELECT MIN(Column1)

FROM Table1

If we use the Customers table from our previous chapters, we can select the lowest date of birth with the

following SQL MIN expression:

SELECT MIN(DOB) AS MinDOB

FROM Customers

AVG Command

The SQL AVG aggregate function selects the average value for certain table column.

Have a look at the SQL AVG syntax:

SELECT AVG(Column1)

FROM Table1

If we want to find out what is the average SaleAmount in the Sales table, we will use the following SQL AVG

statement:

SELECT AVG(SaleAmount) AS AvgSaleAmount

FROM Sales

which will result in the following dataset:

AvgSaleAmount

$195.73

SUM Command

The SQL SUM aggregate function allows selecting the total for a numeric column.

The SQL SUM syntax is displayed below:

SELECT SUM(Column1)

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FROM Table1

We are going to use the Sales table to illustrate the use of SQL SUM clause:

Sales:

CustomerID Date SaleAmount

2 5/6/2004 $100.22

1 5/7/2004 $99.95

3 5/7/2004 $122.95

3 5/13/2004 $100.00

4 5/22/2004 $555.55

Consider the following SQL SUM statement:

SELECT SUM(SaleAmount)

FROM Sales

This SQL statement will return the sum of all SaleAmount fields and the result of it will be:

SaleAmount

$978.67

Of course you can specify search criteria using the SQL WHERE clause in your SQL SUM statement. If you want

to select the total sales for customer with CustomerID = 3, you will use the following SQL SUM statement:

SELECT SUM(SaleAmount)

FROM Sales

WHERE CustomerID = 3

The result will be:

SaleAmount

$222.95

GROUP BY Command

The SQL GROUP BY statement is used along with the SQL aggregate functions like SUM to provide means of

grouping the result dataset by certain database table column(s).

The best way to explain how and when to use the SQL GROUP BY statement is by example, and that’s what

we are going to do.

Consider the following database table called EmployeeHours storing the daily hours for each employee of a

factious company:

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Employee Date Hours










If the manager of the company wants to get the simple sum of all hours worked by all employees, he needs to

execute the following SQL statement:

SELECT SUM (Hours)

FROM EmployeeHours

But what if the manager wants to get the sum of all hours for each of his employees?

To do that he need to modify his SQL query and use the SQL GROUP BY statement:

SELECT Employee, SUM (Hours)

FROM EmployeeHours

GROUP BY Employee

The result of the SQL expression above will be the following:

Employee Hours

John Smith 25

Allan Babel 24

Tina Crown 27

As you can see we have only one entry for each employee, because we are grouping by the Employee column.

The SQL GROUP BY clause can be used with other SQL aggregate functions, for example SQL AVG:

SELECT Employee, AVG(Hours)

FROM EmployeeHours

GROUP BY Employee

The result of the SQL statement above will be:

Employee Hours

John Smith 8.33

Allan Babel 8

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Tina Crown 9

In our Employee table we can group by the date column too, to find out what is the total number of hours

worked on each of the dates into the table:

SELECT Date, SUM(Hours)

FROM EmployeeHours

GROUP BY Date

Here is the result of the above SQL expression:

Date Hours

5/6/2004 24

5/7/2004 27

5/8/2004 25

HAVING Command

The SQL HAVING clause is used to restrict conditionally the output of a SQL statement, by a SQL aggregate

function used in your SELECT list of columns.

You can't specify criteria in a SQL WHERE clause against a column in the SELECT list for which SQL aggregate

function is used. For example the following SQL statement will generate an error:


FROM EmployeeHours

WHERE SUM (Hours) > 24

GROUP BY Employee

The SQL HAVING clause is used to do exactly this, to specify a condition for an aggregate function which is

used in your query:


FROM EmployeeHours

GROUP BY Employee

HAVING SUM (Hours) > 24

The above SQL statement will select all employees and the sum of their respective hours, as long as this sum is

greater than 24. The result of the SQL HAVING clause can be seen below:

Employee Hours

John Smith 25Tina Crown 27

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JOIN Command

The SQL JOIN clause is used whenever we have to select data from 2 or more tables.

To be able to use SQL JOIN clause to extract data from 2 (or more) tables, we need a relationship between

certain columns in these tables.

We are going to illustrate our SQL JOIN example with the following 2 tables:

Customers:

CustomerID FirstName LastName Email DOB Phone

1 John Smith [email protected] 2/4/1968 626 222-2222

2 Steven Goldfish [email protected] 4/4/1974 323 455-4545

3 Paula Brown [email protected] 5/24/1978 416 323-3232

4 James Smith [email protected] 20/10/1980 416 323-8888

Sales:


2 5/6/2004 $100.22

1 5/7/2004 $99.95

3 5/7/2004 $122.95

3 5/13/2004 $100.00

4 5/22/2004 $555.55

As you can see those 2 tables have common field called CustomerID and thanks to that we can extract

information from both tables by matching their CustomerID columns.

Consider the following SQL statement:

SELECT Customers.FirstName, Customers.LastName, SUM(Sales.SaleAmount) AS SalesPerCustomer

FROM Customers, Sales

WHERE Customers.CustomerID = Sales.CustomerID

GROUP BY Customers.FirstName, Customers.LastName

The SQL expression above will select all distinct customers (their first and last names) and the total respective

amount of dollars they have spent.

The SQL JOIN condition has been specified after the SQL WHERE clause and says that the 2 tables have to be

matched by their respective CustomerID columns.

Here is the result of this SQL statement:

FirstName LastName SalesPerCustomers

John Smith $99.95

Steven Goldfish $100.22

Paula Brown $222.95

James Smith $555.55

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The SQL statement above can be re-written using the SQL JOIN clause like this:


FROM Customers JOIN Sales

ON Customers.CustomerID = Sales.CustomerID


There are 2 types of SQL JOINS – INNER JOINS and OUTER JOINS. If you don't put INNER or OUTER

keywords in front of the SQL JOIN keyword, then INNER JOIN is used. In short "INNER JOIN" = "JOIN" (note

that different databases have different syntax for their JOIN clauses).

The INNER JOIN will select all rows from both tables as long as there is a match between the columns we are

matching on. In case we have a customer in the Customers table, which still hasn't made any orders (there are

no entries for this customer in the Sales table), this customer will not be listed in the result of our SQL query

above.

If the Sales table has the following rows:


2 5/6/2004 $100.22

1 5/6/2004 $99.95

And we use the same SQL JOIN statement from above:


FROM Customers JOIN Sales

ON Customers.CustomerID = Sales.CustomerID


We'll get the following result:

FirstName LastName SalesPerCustomers

John Smith $99.95

Steven Goldfish $100.22

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