SQL CREATE VIEW Statement

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)

We can query the view above as follows:

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

We can query the view above as follows:

SELECT * FROM [Category Sales For 1997]

We can also add a condition to the query. Now we want to see the total sale only for the category "Beverages":

SELECT * FROM [Category Sales For 1997] WHERE CategoryName='Beverages'

SQL SELECT INTO Statement

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
ON Employees.Employee_ID=Orders.Employee_ID

SQL GROUP BY and HAVING

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

Returns this result:

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

Returns this result:

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

SQL Functions

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

Function	Description
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

Function	Description
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

SQL ALTER TABLE

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:

LastName	FirstName	Address	City
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 Drop Index Table and Database

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

SQL Create Database Table and Index

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, column_name2 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 ON table_name (column_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:

CREATE INDEX PersonIndex 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:

CREATE INDEX PersonIndex
ON Person (LastName, FirstName)