Learn sql queries

SQL Queries
With SQL, we can query a database and have a result set returned.
A query like this:
SELECT LastName FROM Persons
Gives a result set like this:
LastName
Hansen
Svendson
Pettersen
To select the content of columns named "LastName" and "FirstName", from the database table
called "Persons", use a SELECT statement like this:
SELECT LastName,FirstName FROM Persons
The database table "Persons":
LastName FirstName Address City
Hansen Ola Timoteivn 10 Sandnes
Svendson Tove Borgvn 23 Sandnes
Pettersen Kari Storgt 20 Stavanger
The result
LastName FirstName
Hansen Ola
Svendson Tove
Pettersen Kari
To select all columns from the "Persons" table, use a * symbol instead of column names, like this:
SELECT * FROM Persons
Result

To select ALL values from the column named "Company" we use a SELECT statement like this:
SELECT Company FROM Orders
"Orders" table
Company OrderNumber
Sega 3412
W3Schools 2312
Trio 4678
W3Schools 6798
Result
Company
Sega
W3Schools
Trio
W3Schools
To select only DIFFERENT values from the column named "Company" we use a SELECT DISTINCT
statement like this:
SELECT DISTINCT Company FROM Orders
Result:
Company
Sega
W3Schools
Trio
Using the WHERE Clause
To select only the persons living in the city "Sandnes", we add a WHERE clause to the SELECT
statement:
WHERE City='Sandnes'
"Persons" table
LastName FirstName Address City Year
Hansen Ola Timoteivn 10 Sandnes 1951
Svendson Tove Borgvn 23 Sandnes 1978
Svendson Stale Kaivn 18 Sandnes 1980
Pettersen Kari Storgt 20 Stavanger 1960

Result
LastName FirstName Address City Year
Hansen Ola Timoteivn 10 Sandnes 1951
Svendson Tove Borgvn 23 Sandnes 1978
Svendson Stale Kaivn 18 Sandnes 1980
Using Quotes
Note that we have used single quotes around the conditional values in the examples.
SQL uses single quotes around text values (most database systems will also accept double quotes).
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'
The LIKE Condition
The LIKE condition is used to specify a search for a pattern in a column.
Syntax
SELECT column FROM table
WHERE column LIKE pattern
A "%" sign can be used to define wildcards (missing letters in the pattern) both before and after the
pattern.
Using LIKE
The following SQL statement will return persons with first names that start with an 'O':
WHERE FirstName LIKE 'O%'
The following SQL statement will return persons with first names that end with an 'a':

WHERE FirstName LIKE '%a'
The following SQL statement will return persons with first names that contain the pattern 'la':
WHERE FirstName LIKE '%la%'
The INSERT INTO Statement
The INSERT INTO statement is used to insert new rows into a table.
Syntax
INSERT INTO table_name
VALUES (value1, value2,....)
You can also specify the columns for which you want to insert data:
INSERT INTO table_name (column1, column2,...)
Insert a New Row
This "Persons" table:
And this SQL statement:
INSERT INTO Persons
VALUES ('Hetland', 'Camilla', 'Hagabakka 24', 'Sandnes')
Will give this result:
Hetland Camilla Hagabakka 24 Sandnes
Insert Data in Specified Columns
This "Persons" table:

And This SQL statement:
INSERT INTO Persons (LastName, Address)
VALUES ('Rasmussen', 'Storgt 67')
Will give this result:
Rasmussen Storgt 67
The Update Statement
The UPDATE statement is used to modify the data in a table.
Syntax
UPDATE table_name
SET column_name = new_value
WHERE column_name = some_value
Person:
Nilsen Fred Kirkegt 56 Stavanger
Rasmussen Storgt 67
Update one Column in a Row
We want to add a first name to the person with a last name of "Rasmussen":
UPDATE Person SET FirstName = 'Nina'
WHERE LastName = 'Rasmussen'
Result:
Rasmussen Nina Storgt 67
Update several Columns in a Row
We want to change the address and add the name of the city:
UPDATE Person
SET Address = 'Stien 12', City = 'Stavanger'

WHERE LastName = 'Rasmussen'
Result:
Rasmussen Nina Stien 12 Stavanger
The DELETE Statement
The DELETE statement is used to delete rows in a table.
Syntax
DELETE FROM table_name
WHERE column_name = some_value
Person:
Rasmussen Nina Stien 12 Stavanger
Delete a Row
"Nina Rasmussen" is going to be deleted:
DELETE FROM Person WHERE LastName = 'Rasmussen'
Result
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:
or
DELETE * FROM table_name
Sort the Rows
The ORDER BY clause is used to sort the rows.

Orders:
Company OrderNumber
Sega 3412
ABC Shop 5678
W3Schools 6798
W3Schools 2312
Example
To display the company names in alphabetical order:
SELECT Company, OrderNumber FROM Orders
ORDER BY Company
Result:
Company OrderNumber
ABC Shop 5678
Sega 3412
W3Schools 6798
W3Schools 2312
Example
To display the company names in alphabetical order AND the OrderNumber in numerical order:
ORDER BY Company, OrderNumber
Result:
Company OrderNumber
ABC Shop 5678
Sega 3412
W3Schools 2312
W3Schools 6798
Example
To display the company names in reverse alphabetical order:
ORDER BY Company DESC
Result:
Company OrderNumber
W3Schools 6798

W3Schools 2312
Sega 3412
ABC Shop 5678
Example
To display the company names in reverse alphabetical order AND the OrderNumber in numerical
order:
ORDER BY Company DESC, OrderNumber ASC
Result:
Company OrderNumber
W3Schools 2312
W3Schools 6798
Sega 3412
ABC Shop 5678
Notice that there are two equal company names (W3Schools) in the result above. The only time you
will see the second column in ASC order would be when there are duplicated values in the first sort
column, or a handful of nulls.
AND & OR
AND and OR join two or more conditions in a WHERE clause.
The AND operator displays a row if ALL conditions listed are true. The OR operator displays a row if
ANY of the conditions listed are true.
Original Table (used in the examples)
Svendson Stephen Kaivn 18 Sandnes
Example
Use AND to display each person with the first name equal to "Tove", and the last name equal to
"Svendson":
WHERE FirstName='Tove'
AND LastName='Svendson'
Result:

Example
Use OR to display each person with the first name equal to "Tove", or the last name equal to
"Svendson":
WHERE firstname='Tove'
OR lastname='Svendson'
Result:
Example
You can also combine AND and OR (use parentheses to form complex expressions):
SELECT * FROM Persons WHERE
(FirstName='Tove' OR FirstName='Stephen')
AND LastName='Svendson'
Result:
IN
The IN operator may be used if you know the exact value you want to return for at least one of the
columns.
SELECT column_name FROM table_name
WHERE column_name IN (value1,value2,..)
Nordmann Anna Neset 18 Sandnes

Example 1
To display the persons with LastName equal to "Hansen" or "Pettersen", use the following SQL:
WHERE LastName IN ('Hansen','Pettersen')
Result:
BETWEEN ... AND
The BETWEEN ... AND operator selects a range of data between two values. These values can be
numbers, text, or dates.
SELECT column_name FROM table_name
WHERE column_name
BETWEEN value1 AND value2
Example 1
To display the persons alphabetically between (and including) "Hansen" and exclusive "Pettersen",
use the following SQL:
SELECT * FROM Persons WHERE LastName
BETWEEN 'Hansen' AND 'Pettersen'
Result:
IMPORTANT! The BETWEEN...AND operator is treated differently in different databases. With some
databases a person with the LastName of "Hansen" or "Pettersen" will not be listed (BETWEEN..AND
only selects fields that are between and excluding the test values). With some databases a person
with the last name of "Hansen" or "Pettersen" will be listed (BETWEEN..AND selects fields that are
between and including the test values). With other databases a person with the last name of
"Hansen" will be listed, but "Pettersen" will not be listed (BETWEEN..AND 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....AND operator!
Example 2
To display the persons outside the range used in the previous example, use the NOT operator:
SELECT * FROM Persons WHERE LastName
NOT BETWEEN 'Hansen' AND 'Pettersen'
Result:
With SQL, aliases can be used for column names and table names.
Column Name Alias
The syntax is:
SELECT column AS column_alias FROM table
Table Name Alias
The syntax is:
SELECT column FROM table AS table_alias
Example: Using a Column Alias
This table (Persons):
And this SQL:
SELECT LastName AS Family, FirstName AS Name
FROM Persons
Returns this result:

Family Name
Hansen Ola
Svendson Tove
Pettersen Kari
Example: Using a Table Alias
This table (Persons):
And this SQL:
SELECT LastName, FirstName
FROM Persons AS Employees
Table Employees:
LastName FirstName
Hansen Ola
Svendson Tove
Pettersen Kari
Joins and Keys
Sometimes we have to select data from two or more tables to make our result complete. We have
to perform a join.
Tables in a database can be related to each other with keys. A primary key is a column 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.
In the "Employees" table below, the "Employee_ID" column is the primary key, meaning that no
two rows can have the same Employee_ID. The Employee_ID distinguishes two persons even if they
have the same name.
When you look at the example tables below, notice that:
• The "Employee_ID" column is the primary key of the "Employees" table
• The "Prod_ID" column is the primary key of the "Orders" table
• The "Employee_ID" column in the "Orders" table is used to refer to the persons in the
"Employees" table without using their names
Employees:

Employee_ID Name
01 Hansen, Ola
02 Svendson, Tove
03 Svendson, Stephen
04 Pettersen, Kari
Orders:
Prod_ID Product Employee_ID
234 Printer 01
657 Table 03
865 Chair 03
Referring to Two Tables
We can select data from two tables by referring to two tables, like this:
Example
Who has ordered a product, and what did they order?
SELECT Employees.Name, Orders.Product
FROM Employees, Orders
WHERE Employees.Employee_ID=Orders.Employee_ID
Result
Name Product
Hansen, Ola Printer
Svendson, Stephen Table
Svendson, Stephen Chair
Example
Who ordered a printer?
SELECT Employees.Name
FROM Employees, Orders
WHERE Employees.Employee_ID=Orders.Employee_ID
AND Orders.Product='Printer'
Result
Name
Hansen, Ola
Using Joins

OR we can select data from two tables with the JOIN keyword, like this:
Example INNER JOIN
Syntax
SELECT field1, field2, field3
FROM first_table
INNER JOIN second_table
ON first_table.keyfield = second_table.foreign_keyfield
Who has ordered a product, and what did they order?
FROM Employees
INNER JOIN Orders
ON Employees.Employee_ID=Orders.Employee_ID
The INNER JOIN returns all rows from both tables where there is a match. If there are rows in
Employees that do not have matches in Orders, those rows will not be listed.
Result
Name Product
Hansen, Ola Printer
Example LEFT JOIN
Syntax
FROM first_table
LEFT JOIN second_table
List all employees, and their orders - if any.
FROM Employees
LEFT JOIN Orders
The LEFT JOIN returns all the rows from the first table (Employees), even if there are no matches in
the second table (Orders). If there are rows in Employees that do not have matches in Orders,
those rows also will be listed.
Result
Name Product

Hansen, Ola Printer
Svendson, Tove
Pettersen, Kari
Example RIGHT JOIN
Syntax
FROM first_table
RIGHT JOIN second_table
List all orders, and who has ordered - if any.
FROM Employees
RIGHT JOIN Orders
The RIGHT JOIN returns all the rows from the second table (Orders), even if there are no matches
in the first table (Employees). If there had been any rows in Orders that did not have matches in
Employees, those rows also would have been listed.
Result
Name Product
Hansen, Ola Printer
Example
Who ordered a printer?
SELECT Employees.Name
FROM Employees
INNER JOIN Orders
WHERE Orders.Product = 'Printer'
Result
Name
Hansen, Ola
UNION

The UNION command is used to select related information from two tables, much like the JOIN
command. However, when using the UNION command all selected columns need to be of the same
data type.
Note: With UNION, only distinct values are selected.
SQL Statement 1
UNION
SQL Statement 2
Employees_Norway:
E_ID E_Name
01 Hansen, Ola
02 Svendson, Tove
04 Pettersen, Kari
Employees_USA:
E_ID E_Name
01 Turner, Sally
02 Kent, Clark
04 Scott, Stephen
Using the UNION Command
Example
List all different employee names in Norway and USA:
SELECT E_Name FROM Employees_Norway
UNION
SELECT E_Name FROM Employees_USA
Result
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 is listed. The UNION
command only selects distinct values.
UNION ALL
The UNION ALL command is equal to the UNION command, except that UNION ALL selects all
values.
SQL Statement 1
UNION ALL
SQL Statement 2
Using the UNION ALL Command
Example
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
Create a Database
To create a database:
CREATE DATABASE database_name
Create a Table
To create a table in a database:
CREATE TABLE table_name
(
column_name1 data_type,

.......
)
Example
This example demonstrates how you can create a table named "Person", with four columns. The
column names will be "LastName", "FirstName", "Address", and "Age":
CREATE TABLE Person
(
LastName varchar,
FirstName varchar,
Address varchar,
Age int
)
This example demonstrates how you can specify a maximum length for some columns:
CREATE TABLE Person
(
LastName varchar(30),
FirstName varchar,
Address varchar,
Age int(3)
)
The data type specifies what type of data the column can hold. The table below contains the most
common data types in SQL:
Data Type Description
integer(size)
int(size)
smallint(size)
tinyint(size)
Hold integers only. The maximum number of digits are specified in
parenthesis.
decimal(size,d)
numeric(size,d)
Hold numbers with fractions. The maximum number of digits are
specified in "size". The maximum number of digits to the right of the
decimal is specified in "d".
char(size) Holds a fixed length string (can contain letters, numbers, and special
characters). The fixed size is specified in parenthesis.
varchar(size) Holds a variable length string (can contain letters, numbers, and
special characters). The maximum size is specified in parenthesis.
date(yyyymmdd) Holds a date
Create Index
Indices are created in an existing table to locate rows more quickly and efficiently. It is possible to
create an index on one or more columns of a table, and each index is given a name. The users
cannot see the indexes, they are just used to speed up queries.
Note: Updating a table containing indexes takes more time than updating a table without, this is
because the indexes also need an update. So, it is a good idea to create indexes only on columns
that are often used for a search.

A Unique Index
Creates a unique index on a table. A unique index means that two rows cannot have the same index
value.
CREATE UNIQUE INDEX index_name
ON table_name (column_name)
The "column_name" specifies the column you want indexed.
A Simple Index
Creates a simple index on a table. When the UNIQUE keyword is omitted, duplicate values are
allowed.
CREATE INDEX index_name
The "column_name" specifies the column you want indexed.
Example
This example creates a simple index, named "PersonIndex", on the LastName field of the Person
table:
CREATE INDEX PersonIndex
ON Person (LastName)
If you want to index the values in a column in descending order, you can add the reserved word
DESC after the column name:
ON Person (LastName DESC)
If you want to index more than one column you can list the column names within the parentheses,
separated by commas:
ON Person (LastName, FirstName)
Drop Index
You can delete an existing index in a table with the DROP INDEX statement.
Syntax for Microsoft SQLJet (and Microsoft Access):
DROP INDEX index_name ON table_name
Syntax for MS SQL Server:

DROP INDEX table_name.index_name
Syntax for IBM DB2 and Oracle:
DROP INDEX index_name
Syntax for MySQL:
ALTER TABLE table_name DROP INDEX index_name
Delete a Table or Database
To delete a table (the table structure, attributes, and indexes will also be deleted):
DROP TABLE table_name
To delete a database:
DROP DATABASE database_name
Truncate a Table
What if we only want to get rid of the data inside a table, and not the table itself? Use the
TRUNCATE TABLE command (deletes only the data inside the table):
TRUNCATE TABLE table_name
ALTER TABLE
The ALTER TABLE statement is used to add or drop columns in an existing table.
ALTER TABLE table_name
ADD column_name datatype
ALTER TABLE table_name
DROP COLUMN column_name
Note: Some database systems don't allow the dropping of a column in a database table (DROP
COLUMN column_name).
Person:
LastName FirstName Address
Pettersen Kari Storgt 20
Example

To add a column named "City" in the "Person" table:
ALTER TABLE Person ADD City varchar(30)
Result:
Pettersen Kari Storgt 20
Example
To drop the "Address" column in the "Person" table:
ALTER TABLE Person DROP COLUMN Address
Result:
LastName FirstName City
Pettersen Kari
SQL has a lot of built-in functions for counting and calculations.
Function Syntax
The syntax for built-in SQL functions is:
SELECT function(column) FROM table
Types of Functions
There are several basic types and categories of functions in SQL. The basic types of functions are:
• Aggregate Functions
• Scalar functions
Aggregate functions
Aggregate functions operate against a collection of values, but return a single value.
Note: If used among many other expressions in the item list of a SELECT statement, the SELECT
must have a GROUP BY clause!!
"Persons" table (used in most examples)
Name Age
Hansen, Ola 34
Svendson, Tove 45

Pettersen, Kari 19
Aggregate functions in MS Access
Function Description
AVG(column) Returns the average value of a column
COUNT(column) Returns the number of rows (without a NULL value) of a column
COUNT(*) Returns the number of selected rows
FIRST(column) Returns the value of the first record in a specified field
LAST(column) Returns the value of the last record in a specified field
MAX(column) Returns the highest value of a column
MIN(column) Returns the lowest value of a column
STDEV(column)
STDEVP(column)
SUM(column) Returns the total sum of a column
VAR(column)
VARP(column)
Aggregate functions in SQL Server
AVG(column) Returns the average value of a column
BINARY_CHECKSUM
CHECKSUM
CHECKSUM_AGG
COUNT(column) Returns the number of rows (without a NULL value) of a column
COUNT(*) Returns the number of selected rows
COUNT(DISTINCT column) Returns the number of distinct results
FIRST(column) Returns the value of the first record in a specified field (not
supported in SQLServer2K)
LAST(column) Returns the value of the last record in a specified field (not
supported in SQLServer2K)
MAX(column) Returns the highest value of a column
MIN(column) Returns the lowest value of a column
STDEV(column)
STDEVP(column)
SUM(column) Returns the total sum of a column
VAR(column)
VARP(column)
Scalar functions
Scalar functions operate against a single value, and return a single value based on the input value.
Useful Scalar Functions in MS Access

UCASE(c) Converts a field to upper case
LCASE(c) Converts a field to lower case
MID(c,start[,end]) Extract characters from a text field
LEN(c) Returns the length of a text field
INSTR(c,char) Returns the numeric position of a named character within a text
field
LEFT(c,number_of_char) Return the left part of a text field requested
RIGHT(c,number_of_char) Return the right part of a text field requested
ROUND(c,decimals) Rounds a numeric field to the number of decimals specified
MOD(x,y) Returns the remainder of a division operation
NOW() Returns the current system date
FORMAT(c,format) Changes the way a field is displayed
DATEDIFF(d,date1,date2) Used to perform date calculations
Aggregate functions (like SUM) often need an added GROUP BY functionality.
GROUP BY...
GROUP BY... was added to SQL because aggregate functions (like SUM) return the aggregate of all
column values every time they are called, and without the GROUP BY function it was impossible to
find the sum for each individual group of column values.
The syntax for the GROUP BY function is:
SELECT column,SUM(column) FROM table GROUP BY column
GROUP BY Example
This "Sales" Table:
Company Amount
W3Schools 5500
IBM 4500
W3Schools 7100
And This SQL:
SELECT Company, SUM(Amount) FROM Sales
Company SUM(Amount)
W3Schools 17100
IBM 17100
W3Schools 17100
The above code is invalid because the column returned is not part of an aggregate. A GROUP BY
clause will solve this problem:

SELECT Company,SUM(Amount) FROM Sales
GROUP BY Company
Company SUM(Amount)
W3Schools 12600
IBM 4500
HAVING...
HAVING... was added to SQL because the WHERE keyword could not be used against aggregate
functions (like SUM), and without HAVING... it would be impossible to test for result conditions.
The syntax for the HAVING function is:
SELECT column,SUM(column) FROM table
GROUP BY column
HAVING SUM(column) condition value
This "Sales" Table:
Company Amount
W3Schools 5500
IBM 4500
W3Schools 7100
This SQL:
SELECT Company,SUM(Amount) FROM Sales
GROUP BY Company
HAVING SUM(Amount)>10000
Returns this result
Company SUM(Amount)
W3Schools 12600
The SELECT INTO Statement
The SELECT INTO statement is most often used to create backup copies of tables or for archiving
records.
Syntax
SELECT column_name(s) INTO newtable [IN externaldatabase]
FROM source

Make a Backup Copy
The following example makes a backup copy of the "Persons" table:
SELECT * INTO Persons_backup
FROM Persons
The IN clause can be used to copy tables into another database:
SELECT Persons.* INTO Persons IN 'Backup.mdb'
FROM Persons
If you only want to copy a few fields, you can do so by listing them after the SELECT statement:
SELECT LastName,FirstName INTO Persons_backup
FROM Persons
You can also add a WHERE clause. The following example creates a "Persons_backup" table with
two columns (FirstName and LastName) by extracting the persons who lives in "Sandnes" from the
"Persons" table:
SELECT LastName,Firstname INTO Persons_backup
FROM Persons
WHERE City='Sandnes'
Selecting data from more than one table is also possible. The following example creates a new table
"Empl_Ord_backup" that contains data from the two tables Employees and Orders:
SELECT Employees.Name,Orders.Product
INTO Empl_Ord_backup
FROM Employees
INNER JOIN Orders
A view is a virtual table based on the result-set of a SELECT statement.
What is a View?
In SQL, a VIEW is a virtual table based on the result-set of a SELECT statement.
A view contains rows and columns, just like a real table. The fields in a view are fields from one or
more real tables in the database. You can add SQL functions, WHERE, and JOIN statements to a
view and present the data as if the data were coming from a single table.
Note: The database design and structure will NOT be affected by the functions, where, or join
statements in a view.
Syntax
CREATE VIEW view_name AS
SELECT column_name(s)

FROM table_name
WHERE condition
Note: The database does not store the view data! The database engine recreates the data, using
the view's SELECT statement, every time a user queries a view.
Using Views
A view could be used from inside a query, a stored procedure, or from inside another view. By
adding functions, joins, etc., to a view, it allows you to present exactly the data you want to the
user.
The sample database Northwind has some views installed by default. The view "Current Product
List" lists all active products (products that are not discontinued) from the Products table. The view
is created with the following SQL:
CREATE VIEW [Current Product List] AS
SELECT ProductID,ProductName
FROM Products
WHERE Discontinued=No
We can query the view above as follows:
SELECT * FROM [Current Product List]
Another view from the Northwind sample database selects every product in the Products table that
has a unit price that is higher than the average unit price:
CREATE VIEW [Products Above Average Price] AS
SELECT ProductName,UnitPrice
FROM Products
WHERE UnitPrice>(SELECT AVG(UnitPrice) FROM Products)
SELECT * FROM [Products Above Average Price]
Another example view from the Northwind database calculates the total sale for each category in
1997. Note that this view selects its data from another view called "Product Sales for 1997":
CREATE VIEW [Category Sales For 1997] AS
SELECT DISTINCT CategoryName,Sum(ProductSales) AS CategorySales
FROM [Product Sales for 1997]
GROUP BY CategoryName
SELECT * FROM [Category Sales For 1997]

We can also add a condition to the query. Now we want to see the total sale only for the category
"Beverages":
SELECT * FROM [Category Sales For 1997]
WHERE CategoryName='Beverages'
SQL Syntax
Statement Syntax
AND / OR SELECT column_name(s)
FROM table_name
WHERE condition
AND|OR condition
ALTER TABLE (add column) ALTER TABLE table_name
ADD column_name datatype
ALTER TABLE (drop column) ALTER TABLE table_name
DROP COLUMN column_name
AS (alias for column) SELECT column_name AS column_alias
FROM table_name
AS (alias for table) SELECT column_name
FROM table_name AS table_alias
BETWEEN SELECT column_name(s)
FROM table_name
WHERE column_name
BETWEEN value1 AND value2
CREATE DATABASE CREATE DATABASE database_name
CREATE INDEX CREATE INDEX index_name
CREATE TABLE CREATE TABLE table_name
(
.......
)
CREATE UNIQUE INDEX CREATE UNIQUE INDEX index_name
CREATE VIEW CREATE VIEW view_name AS
FROM table_name
WHERE condition
DELETE FROM DELETE FROM table_name
(Note: Deletes the entire table!!)
or
WHERE condition
DROP DATABASE DROP DATABASE database_name
DROP INDEX DROP INDEX table_name.index_name
DROP TABLE DROP TABLE table_name
GROUP BY SELECT column_name1,SUM(column_name2)
FROM table_name
GROUP BY column_name1
HAVING SELECT column_name1,SUM(column_name2)

FROM table_name
GROUP BY column_name1
HAVING SUM(column_name2) condition value
IN SELECT column_name(s)
FROM table_name
WHERE column_name
IN (value1,value2,..)
INSERT INTO INSERT INTO table_name
or
INSERT INTO table_name
(column_name1, column_name2,...)
LIKE SELECT column_name(s)
FROM table_name
WHERE column_name
LIKE pattern
ORDER BY SELECT column_name(s)
FROM table_name
ORDER BY column_name [ASC|DESC]
SELECT SELECT column_name(s)
FROM table_name
SELECT * SELECT *
FROM table_name
SELECT DISTINCT SELECT DISTINCT column_name(s)
FROM table_name
SELECT INTO
(used to create backup copies of
tables)
SELECT *
INTO new_table_name
FROM original_table_name
or
INTO new_table_name
FROM original_table_name
TRUNCATE TABLE
(deletes only the data inside the
table)
TRUNCATE TABLE table_name
UPDATE UPDATE table_name
SET column_name=new_value
[, column_name=new_value]
WHERE column_name=some_value
WHERE SELECT column_name(s)
FROM table_name
WHERE condition

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