SQL Commands

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BASIC SQL COMMANDS ( Structured Query Language )

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CONTENTS

1. SQL DATABASE TABLE ...................................................................................... 03

2. SQL SELECT............................................................................................................ 03

3. SQL SELECT INTO ................................................................................................ 03

4. SQL DISTINCT ........................................................................................................ 04

5. SQL WHERE ............................................................................................................ 04-05

6. SQL LIKE .................................................................................................................. 06

7. SQL INSERT INTO ................................................................................................. 07-08

8. SQL UPDATE ........................................................................................................... 08

9. SQL DELETE ........................................................................................................... 09

10. SQL ORDER BY ...................................................................................................... 09-10

11. SQL OR & AND ....................................................................................................... 10-11

12. SQL IN ....................................................................................................................... 11-12

13. SQL BETWEEN ....................................................................................................... 12-13

14. SQL ALIASES .......................................................................................................... 13

15. SQL COUNT ............................................................................................................. 13-14

16. SQL MAX .................................................................................................................. 14

17. SQL MIN ................................................................................................................... 14

18. SQL AVG ................................................................................................................... 14-15

19. SQL SUM ................................................................................................................... 15

20. SQL GROUP BY ...................................................................................................... 16-17

21. SQL HAVING ........................................................................................................... 17

22. SQL JOIN .................................................................................................................. 18-20

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SQL Commands

SQL Database Table

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

SELECT

The SQL SELECT statement is used to select data from a SQL database table.

Please have a look at the general SQL SELECT syntax:

SELECT Column1, Column2, Column3,

FROM Table1

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

be returned in your result set.

SELECT *

FROM Table1

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

columns are returned.

SELECT INTO

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.

SELECT Column1, Column2, Column3,

INTO Table2

FROM Table1

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

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DISTINCT

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.






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

LastName

Smith

Goldfish

Brown

WHERE

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:




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

LastName = 'Smith'

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%'

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

Between (Defines a range)

SELECT *

FROM Customers

WHERE DOB BETWEEN '1/1/1970' AND '1/1/1975'

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LIKE

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.

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%'

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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 (%)





INSERT INTO

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 inserted in 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:

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

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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

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






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 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:






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DELETE

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

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

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

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ORDER BY DOB DESC

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






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


ORDER 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

AND & OR

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:


WHERE 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

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:

SELECT *

FROM EmployeeHours

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

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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

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:






Consider the following SQL BETWEEN statement:

SELECT *

FROM Customers

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

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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

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:

Employee

John Smith

Allan Babel

Tina Crown

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

COUNT

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

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NumberOfCustomers

4

MAX

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

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

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

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$195.73

SUM

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

The SQL SUM syntax is displayed below

SELECT SUM(Column1)

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

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GROUP BY

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

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

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The result of the SQL statement above will be

Employee Hours

John Smith 8.33

Allan Babel 8

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

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 25

Tina Crown 27

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JOIN

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


SalesPerCustomer

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


SalesPerCustomer

FROM Customers JOIN Sales



We'll get the following result


John Smith $99.95


Even though Paula and James are listed as customers in the Customers table they won't be displayed

because they haven't purchased anything yet

But what if you want to display all the customers and their sales, no matter if they have ordered

something or not? We’ll do that with the help of SQL OUTER JOIN clause

The second type of SQL JOIN is called SQL OUTER JOIN and it has 2 sub-types called LEFT

OUTER JOIN and RIGHT OUTER JOIN

The LEFT OUTER JOIN or simply LEFT JOIN (you can omit the OUTER keyword in most

databases), selects all the rows from the first table listed after the FROM clause, no matter if they have

matches in the second table

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If we slightly modify our last SQL statement to


SalesPerCustomer

FROM Customers LEFT JOIN Sales



and the Sales table still has the following rows:


2 5/6/2004 $100.22

1 5/6/2004 $99.95

The result will be the following


John Smith $99.95


Paula Brown NULL

James Smith NULL

As you can see we have selected everything from the Customers (first table). For all rows from

Customers, which don’t have a match in the Sales (second table), the SalesPerCustomer column has

amount NULL (NULL means a column contains nothing).

The RIGHT OUTER JOIN or just RIGHT JOIN behaves exactly as SQL LEFT JOIN, except that

it returns all rows from the second table (the right table in our SQL JOIN statement)

Documents

SQL Commands