Thursday, February 11, 2016

SQL - Guide -Part II

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)
)

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)

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

SQL PRIMARY KEY Constraint

SQL PRIMARY KEY Constraint

The PRIMARY KEY constraint uniquely identifies each record in a database table.
Primary keys must contain unique values.
A primary key column cannot contain NULL values.
Each table should have a primary key, and each table can have only ONE primary key.

SQL PRIMARY KEY Constraint on CREATE TABLE

The following SQL creates a PRIMARY KEY 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),
PRIMARY KEY (P_Id)
)
SQL Server / Oracle / MS Access:
CREATE TABLE Persons
(
P_Id int NOT NULL PRIMARY KEY,
LastName varchar(255) NOT NULL,
FirstName varchar(255),
Address varchar(255),
City varchar(255)
)
To allow naming of a PRIMARY KEY constraint, and for defining a PRIMARY KEY 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 pk_PersonID PRIMARY KEY (P_Id,LastName)
)

SQL PRIMARY KEY Constraint on ALTER TABLE

To create a PRIMARY KEY 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 PRIMARY KEY (P_Id)
To allow naming of a PRIMARY KEY constraint, and for defining a PRIMARY KEY constraint on multiple columns, use the following SQL syntax:
MySQL / SQL Server / Oracle / MS Access:
ALTER TABLE Persons
ADD CONSTRAINT pk_PersonID PRIMARY KEY (P_Id,LastName)
Note: If you use the ALTER TABLE statement to add a primary key, the primary key column(s) must already have been declared to not contain NULL values (when the table was first created).

To DROP a PRIMARY KEY Constraint

To drop a PRIMARY KEY constraint, use the following SQL:
MySQL:
ALTER TABLE Persons
DROP PRIMARY KEY
SQL Server / Oracle / MS Access:
ALTER TABLE Persons
DROP CONSTRAINT pk_PersonID

SQL FOREIGN KEY Constraint

SQL FOREIGN KEY Constraint

A FOREIGN KEY in one table points to a PRIMARY KEY in another table.
Let's illustrate the foreign key with an example. Look at the following two tables:
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
2
4
24562
1
Note that the "P_Id" column in the "Orders" table points to the "P_Id" column in the "Persons" table.
The "P_Id" column in the "Persons" table is the PRIMARY KEY in the "Persons" table.
The "P_Id" column in the "Orders" table is a FOREIGN KEY in the "Orders" table.
The FOREIGN KEY constraint is used to prevent actions that would destroy links between tables.
The FOREIGN KEY constraint also prevents that invalid data form being inserted into the foreign key column, because it has to be one of the values contained in the table it points to.

SQL FOREIGN KEY Constraint on CREATE TABLE

The following SQL creates a FOREIGN KEY on the "P_Id" column when the "Orders" table is created:
MySQL:
CREATE TABLE Orders
(
O_Id int NOT NULL,
OrderNo int NOT NULL,
P_Id int,
PRIMARY KEY (O_Id),
FOREIGN KEY (P_Id) REFERENCES Persons(P_Id)
)
SQL Server / Oracle / MS Access:
CREATE TABLE Orders
(
O_Id int NOT NULL PRIMARY KEY,
OrderNo int NOT NULL,
P_Id int FOREIGN KEY REFERENCES Persons(P_Id)
)
To allow naming of a FOREIGN KEY constraint, and for defining a FOREIGN KEY constraint on multiple columns, use the following SQL syntax:
MySQL / SQL Server / Oracle / MS Access:
CREATE TABLE Orders
(
O_Id int NOT NULL,
OrderNo int NOT NULL,
P_Id int,
PRIMARY KEY (O_Id),
CONSTRAINT fk_PerOrders FOREIGN KEY (P_Id)
REFERENCES Persons(P_Id)
)

SQL FOREIGN KEY Constraint on ALTER TABLE

To create a FOREIGN KEY constraint on the "P_Id" column when the "Orders" table is already created, use the following SQL:
MySQL / SQL Server / Oracle / MS Access:
ALTER TABLE Orders
ADD FOREIGN KEY (P_Id)
REFERENCES Persons(P_Id)
To allow naming of a FOREIGN KEY constraint, and for defining a FOREIGN KEY constraint on multiple columns, use the following SQL syntax:
MySQL / SQL Server / Oracle / MS Access:
ALTER TABLE Orders
ADD CONSTRAINT fk_PerOrders
FOREIGN KEY (P_Id)
REFERENCES Persons(P_Id)

To DROP a FOREIGN KEY Constraint

To drop a FOREIGN KEY constraint, use the following SQL:
MySQL:
ALTER TABLE Orders
DROP FOREIGN KEY fk_PerOrders
SQL Server / Oracle / MS Access:
ALTER TABLE Orders
DROP CONSTRAINT fk_PerOrders

SQL CHECK Constraint

SQL CHECK Constraint

The CHECK constraint is used to limit the value range that can be placed in a column.
If you define a CHECK constraint on a single column it allows only certain values for this column.
If you define a CHECK constraint on a table it can limit the values in certain columns based on values in other columns in the row.

SQL CHECK Constraint on CREATE TABLE

The following SQL creates a CHECK constraint on the "P_Id" column when the "Persons" table is created. The CHECK constraint specifies that the column "P_Id" must only include integers greater than 0.
My SQL:
CREATE TABLE Persons
(
P_Id int NOT NULL,
LastName varchar(255) NOT NULL,
FirstName varchar(255),
Address varchar(255),
City varchar(255),
CHECK (P_Id>0)
)
SQL Server / Oracle / MS Access:
CREATE TABLE Persons
(
P_Id int NOT NULL CHECK (P_Id>0),
LastName varchar(255) NOT NULL,
FirstName varchar(255),
Address varchar(255),
City varchar(255)
)
To allow naming of a CHECK constraint, and for defining a CHECK 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 chk_Person CHECK (P_Id>0 AND City='Sandnes')
)

SQL CHECK Constraint on ALTER TABLE

To create a CHECK 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 CHECK (P_Id>0)
To allow naming of a CHECK constraint, and for defining a CHECK constraint on multiple columns, use the following SQL syntax:
MySQL / SQL Server / Oracle / MS Access:
ALTER TABLE Persons
ADD CONSTRAINT chk_Person CHECK (P_Id>0 AND City='Sandnes')

To DROP a CHECK Constraint

To drop a CHECK constraint, use the following SQL:
SQL Server / Oracle / MS Access:
ALTER TABLE Persons
DROP CONSTRAINT chk_Person

SQL DEFAULT Constraint

SQL DEFAULT Constraint

The DEFAULT constraint is used to insert a default value into a column.
The default value will be added to all new records, if no other value is specified.

SQL DEFAULT Constraint on CREATE TABLE

The following SQL creates a DEFAULT constraint on the "City" column when the "Persons" table is created:
My SQL / 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) DEFAULT 'Sandnes'
)
The DEFAULT constraint can also be used to insert system values, by using functions like GETDATE():
CREATE TABLE Orders
(
O_Id int NOT NULL,
OrderNo int NOT NULL,
P_Id int,
OrderDate date DEFAULT GETDATE()
)

SQL DEFAULT Constraint on ALTER TABLE

To create a DEFAULT constraint on the "City" column when the table is already created, use the following SQL:
MySQL:
ALTER TABLE Persons
ALTER City SET DEFAULT 'SANDNES'
SQL Server / Oracle / MS Access:
ALTER TABLE Persons
ALTER COLUMN City SET DEFAULT 'SANDNES'

To DROP a DEFAULT Constraint

To drop a DEFAULT constraint, use the following SQL:
MySQL:
ALTER TABLE Persons
ALTER City DROP DEFAULT
SQL Server / Oracle / MS Access:
ALTER TABLE Persons
ALTER COLUMN City DROP DEFAULT

SQL CREATE INDEX Statement

The CREATE INDEX statement is used to create indexes in tables.
Indexes allow the database application to find data fast; without reading the whole table.

Indexes

An index can be created in a table to find data more quickly and efficiently.
The users cannot see the indexes, they are just used to speed up searches/queries.
Note: Updating a table with indexes takes more time than updating a table without (because the indexes also need an update). So you should only create indexes on columns (and tables) that will be frequently searched against.

SQL CREATE INDEX Syntax

Creates an index on a table. Duplicate values are allowed:
CREATE INDEX index_name
ON table_name (column_name)

SQL CREATE UNIQUE INDEX Syntax

Creates a unique index on a table. Duplicate values are not allowed:
CREATE UNIQUE INDEX index_name
ON table_name (column_name)
Note: The syntax for creating indexes varies amongst different databases. Therefore: Check the syntax for creating indexes in your database.

CREATE INDEX Example

The SQL statement below creates an index named "PIndex" on the "LastName" column in the "Persons" table:
CREATE INDEX PIndex
ON Persons (LastName)
If you want to create an index on a combination of columns, you can list the column names within the parentheses, separated by commas:
CREATE INDEX PIndex
ON Persons (LastName, FirstName)

SQL DROP INDEX, DROP TABLE, and DROP DATABASE

Indexes, tables, and databases can easily be deleted/removed with the DROP statement.

The DROP INDEX Statement

The DROP INDEX statement is used to delete an index in a table.

DROP INDEX Syntax for MS Access:

DROP INDEX index_name ON table_name

DROP INDEX Syntax for MS SQL Server:

DROP INDEX table_name.index_name

DROP INDEX Syntax for DB2/Oracle:

DROP INDEX index_name

DROP INDEX Syntax for MySQL:

ALTER TABLE table_name DROP INDEX index_name

The DROP TABLE Statement

The DROP TABLE statement is used to delete a table.
DROP TABLE table_name

The DROP DATABASE Statement

The DROP DATABASE statement is used to delete a database.
DROP DATABASE database_name

The TRUNCATE TABLE Statement

What if we only want to delete the data inside the table, and not the table itself?
Then, use the TRUNCATE TABLE statement:
TRUNCATE TABLE table_name

SQL ALTER TABLE Statement

The ALTER TABLE Statement

The ALTER TABLE statement is used to add, delete, or modify columns in an existing table.

SQL ALTER TABLE Syntax

To add a column in a table, use the following syntax:
ALTER TABLE table_name
ADD column_name datatype
To delete a column in a table, use the following syntax (notice that some database systems don't allow deleting a column):
ALTER TABLE table_name
DROP COLUMN column_name
To change the data type of a column in a table, use the following syntax:
ALTER TABLE table_name
ALTER COLUMN column_name datatype

SQL ALTER TABLE Example

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
Now we want to add a column named "DateOfBirth" in the "Persons" table.
We use the following SQL statement:
ALTER TABLE Persons
ADD DateOfBirth date
Notice that the new column, "DateOfBirth", is of type date and is going to hold a date. 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.
The "Persons" table will now like this:
P_Id
LastName
FirstName
Address
City
DateOfBirth
1
Hansen
Ola
Timoteivn 10
Sandnes

2
Svendson
Tove
Borgvn 23
Sandnes

3
Pettersen
Kari
Storgt 20
Stavanger


Change Data Type Example

Now we want to change the data type of the column named "DateOfBirth" in the "Persons" table.
We use the following SQL statement:
ALTER TABLE Persons
ALTER COLUMN DateOfBirth year
Notice that the "DateOfBirth" column is now of type year and is going to hold a year in a two-digit or four-digit format.

DROP COLUMN Example

Next, we want to delete the column named "DateOfBirth" in the "Persons" table.
We use the following SQL statement:
ALTER TABLE Persons
DROP COLUMN DateOfBirth
The "Persons" table will now 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

SQL AUTO INCREMENT Field

Auto-increment allows a unique number to be generated when a new record is inserted into a table.

AUTO INCREMENT a Field

Very often we would like the value of the primary key field to be created automatically every time a new record is inserted.
We would like to create an auto-increment field in a table.

Syntax for MySQL

The following SQL statement defines the "P_Id" column to be an auto-increment primary key field in the "Persons" table:
CREATE TABLE Persons
(
P_Id int NOT NULL AUTO_INCREMENT,
LastName varchar(255) NOT NULL,
FirstName varchar(255),
Address varchar(255),
City varchar(255),
PRIMARY KEY (P_Id)
)
MySQL uses the AUTO_INCREMENT keyword to perform an auto-increment feature.
By default, the starting value for AUTO_INCREMENT is 1, and it will increment by 1 for each new record.
To let the AUTO_INCREMENT sequence start with another value, use the following SQL statement:
ALTER TABLE Persons AUTO_INCREMENT=100
To insert a new record into the "Persons" table, we will not have to specify a value for the "P_Id" column (a unique value will be added automatically):
INSERT INTO Persons (FirstName,LastName)
VALUES ('Lars','Monsen')
The SQL statement above would insert a new record into the "Persons" table. The "P_Id" column would be assigned a unique value. The "FirstName" column would be set to "Lars" and the "LastName" column would be set to "Monsen".

Syntax for SQL Server

The following SQL statement defines the "P_Id" column to be an auto-increment primary key field in the "Persons" table:
CREATE TABLE Persons
(
P_Id int PRIMARY KEY IDENTITY,
LastName varchar(255) NOT NULL,
FirstName varchar(255),
Address varchar(255),
City varchar(255)
)
The MS SQL Server uses the IDENTITY keyword to perform an auto-increment feature.
By default, the starting value for IDENTITY is 1, and it will increment by 1 for each new record.
To specify that the "P_Id" column should start at value 10 and increment by 5, change the identity to IDENTITY(10,5).
To insert a new record into the "Persons" table, we will not have to specify a value for the "P_Id" column (a unique value will be added automatically):
INSERT INTO Persons (FirstName,LastName)
VALUES ('Lars','Monsen')
The SQL statement above would insert a new record into the "Persons" table. The "P_Id" column would be assigned a unique value. The "FirstName" column would be set to "Lars" and the "LastName" column would be set to "Monsen".

Syntax for Access

The following SQL statement defines the "P_Id" column to be an auto-increment primary key field in the "Persons" table:
CREATE TABLE Persons
(
P_Id PRIMARY KEY AUTOINCREMENT,
LastName varchar(255) NOT NULL,
FirstName varchar(255),
Address varchar(255),
City varchar(255)
)
The MS Access uses the AUTOINCREMENT keyword to perform an auto-increment feature.
By default, the starting value for AUTOINCREMENT is 1, and it will increment by 1 for each new record.
To specify that the "P_Id" column should start at value 10 and increment by 5, change the autoincrement to AUTOINCREMENT(10,5).
To insert a new record into the "Persons" table, we will not have to specify a value for the "P_Id" column (a unique value will be added automatically):
INSERT INTO Persons (FirstName,LastName)
VALUES ('Lars','Monsen')
The SQL statement above would insert a new record into the "Persons" table. The "P_Id" column would be assigned a unique value. The "FirstName" column would be set to "Lars" and the "LastName" column would be set to "Monsen".

Syntax for Oracle

In Oracle the code is a little bit more tricky.
You will have to create an auto-increment field with the sequence object (this object generates a number sequence).
Use the following CREATE SEQUENCE syntax:
CREATE SEQUENCE seq_person
MINVALUE 1
START WITH 1
INCREMENT BY 1
CACHE 10
The code above creates a sequence object called seq_person, that starts with 1 and will increment by 1. It will also cache up to 10 values for performance. The cache option specifies how many sequence values will be stored in memory for faster access.
To insert a new record into the "Persons" table, we will have to use the nextval function (this function retrieves the next value from seq_person sequence):
INSERT INTO Persons (P_Id,FirstName,LastName)
VALUES (seq_person.nextval,'Lars','Monsen')
The SQL statement above would insert a new record into the "Persons" table. The "P_Id" column would be assigned the next number from the seq_person sequence. The "FirstName" column would be set to "Lars" and the "LastName" column would be set to "Monsen".

SQL Views

A view is a virtual table.
This chapter shows how to create, update, and delete a view.

SQL CREATE VIEW Statement

In SQL, a view is a virtual table based on the result-set of an SQL 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 one single table.

SQL CREATE VIEW Syntax

CREATE VIEW view_name AS
SELECT column_name(s)
FROM table_name
WHERE condition
Note: A view always shows up-to-date data! The database engine recreates the data, using the view's SQL statement, every time a user queries a view.

SQL CREATE VIEW Examples

If you have the Northwind database you can see that it has several 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 in the Northwind sample database selects every product in the "Products" table with a unit price 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 view in 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 Updating a View

You can update a view by using the following syntax:

SQL CREATE OR REPLACE VIEW Syntax

CREATE OR REPLACE VIEW view_name AS
SELECT column_name(s)
FROM table_name
WHERE condition
Now we want to add the "Category" column to the "Current Product List" view. We will update the view with the following SQL:
CREATE VIEW [Current Product List] AS
SELECT ProductID,ProductName,Category
FROM Products
WHERE Discontinued=No

SQL Dropping a View

You can delete a view with the DROP VIEW command.

SQL DROP VIEW Syntax

DROP VIEW view_name

SQL Date Functions

SQL Dates

The most difficult part when working with dates is to be sure that the format of the date you are trying to insert, matches the format of the date column in the database.
As long as your data contains only the date portion, your queries will work as expected. However, if a time portion is involved, it gets complicated.
Before talking about the complications of querying for dates, we will look at the most important built-in functions for working with dates.

MySQL Date Functions

The following table lists the most important built-in date functions in MySQL:
Function
Description
Returns the current date and time
Returns the current date
Returns the current time
Extracts the date part of a date or date/time expression
Returns a single part of a date/time
Adds a specified time interval to a date
Subtracts a specified time interval from a date
Returns the number of days between two dates
Displays date/time data in different formats

SQL Server Date Functions

The following table lists the most important built-in date functions in SQL Server:
Function
Description
Returns the current date and time
Returns a single part of a date/time
Adds or subtracts a specified time interval from a date
Returns the time between two dates
Displays date/time data in different formats

SQL Date Data Types

MySQL comes with the following data types for storing a date or a date/time value in the database:
·        DATE - format YYYY-MM-DD
·        DATETIME - format: YYYY-MM-DD HH:MM:SS
·        TIMESTAMP - format: YYYY-MM-DD HH:MM:SS
·        YEAR - format YYYY or YY
SQL Server comes with the following data types for storing a date or a date/time value in the database:
·        DATE - format YYYY-MM-DD
·        DATETIME - format: YYYY-MM-DD HH:MM:SS
·        SMALLDATETIME - format: YYYY-MM-DD HH:MM:SS
·        TIMESTAMP - format: a unique number
Note: The date types are chosen for a column when you create a new table in your database!
For an overview of all data types available, go to our complete Data Types reference.

SQL Working with Dates

You can compare two dates easily if there is no time component involved!
Assume we have the following "Orders" table:
OrderId
ProductName
OrderDate
1
Geitost
2008-11-11
2
Camembert Pierrot
2008-11-09
3
Mozzarella di Giovanni
2008-11-11
4
Mascarpone Fabioli
2008-10-29
Now we want to select the records with an OrderDate of "2008-11-11" from the table above.
We use the following SELECT statement:
SELECT * FROM Orders WHERE OrderDate='2008-11-11'
The result-set will look like this:
OrderId
ProductName
OrderDate
1
Geitost
2008-11-11
3
Mozzarella di Giovanni
2008-11-11
Now, assume that the "Orders" table looks like this (notice the time component in the "OrderDate" column):
OrderId
ProductName
OrderDate
1
Geitost
2008-11-11 13:23:44
2
Camembert Pierrot
2008-11-09 15:45:21
3
Mozzarella di Giovanni
2008-11-11 11:12:01
4
Mascarpone Fabioli
2008-10-29 14:56:59
If we use the same SELECT statement as above:
SELECT * FROM Orders WHERE OrderDate='2008-11-11'
we will get no result! This is because the query is looking only for dates with no time portion.
Tip: If you want to keep your queries simple and easy to maintain, do not allow time components in your dates!

SQL NULL Values

NULL values represent missing unknown data.
By default, a table column can hold NULL values.
This chapter will explain the IS NULL and IS NOT NULL operators.

SQL NULL Values

If a column in a table is optional, we can insert a new record or update an existing record without adding a value to this column. This means that the field will be saved with a NULL value.
NULL values are treated differently from other values.
NULL is used as a placeholder for unknown or inapplicable values.
Note: It is not possible to compare NULL and 0; they are not equivalent.

SQL Working with NULL Values

Look at the following "Persons" table:
P_Id
LastName
FirstName
Address
City
1
Hansen
Ola

Sandnes
2
Svendson
Tove
Borgvn 23
Sandnes
3
Pettersen
Kari

Stavanger
Suppose that the "Address" column in the "Persons" table is optional. This means that if we insert a record with no value for the "Address" column, the "Address" column will be saved with a NULL value.
How can we test for NULL values?
It is not possible to test for NULL values with comparison operators, such as =, <, or <>.
We will have to use the IS NULL and IS NOT NULL operators instead.

SQL IS NULL

How do we select only the records with NULL values in the "Address" column?
We will have to use the IS NULL operator:
SELECT LastName,FirstName,Address FROM Persons
WHERE Address IS NULL
The result-set will look like this:
LastName
FirstName
Address
Hansen
Ola

Pettersen
Kari

Tip: Always use IS NULL to look for NULL values.

SQL IS NOT NULL

How do we select only the records with no NULL values in the "Address" column?
We will have to use the IS NOT NULL operator:
SELECT LastName,FirstName,Address FROM Persons
WHERE Address IS NOT NULL
The result-set will look like this:
LastName
FirstName
Address
Svendson
Tove
Borgvn 23
In the next chapter we will look at the ISNULL(), NVL(), IFNULL() and COALESCE() functions.

SQL NULL Functions

SQL ISNULL(), NVL(), IFNULL() and COALESCE() Functions

Look at the following "Products" table:
P_Id
ProductName
UnitPrice
UnitsInStock
UnitsOnOrder
1
Jarlsberg
10.45
16
15
2
Mascarpone
32.56
23

3
Gorgonzola
15.67
9
20
Suppose that the "UnitsOnOrder" column is optional, and may contain NULL values.
We have the following SELECT statement:
SELECT ProductName,UnitPrice*(UnitsInStock+UnitsOnOrder)
FROM Products
In the example above, if any of the "UnitsOnOrder" values are NULL, the result is NULL.
Microsoft's ISNULL() function is used to specify how we want to treat NULL values.
The NVL(), IFNULL(), and COALESCE() functions can also be used to achieve the same result.
In this case we want NULL values to be zero.
Below, if "UnitsOnOrder" is NULL it will not harm the calculation, because ISNULL() returns a zero if the value is NULL:
SQL Server / MS Access
SELECT ProductName,UnitPrice*(UnitsInStock+ISNULL(UnitsOnOrder,0))
FROM Products
Oracle
Oracle does not have an ISNULL() function. However, we can use the NVL() function to achieve the same result:
SELECT ProductName,UnitPrice*(UnitsInStock+NVL(UnitsOnOrder,0))
FROM Products
MySQL
MySQL does have an ISNULL() function. However, it works a little bit different from Microsoft's ISNULL() function.
In MySQL we can use the IFNULL() function, like this:
SELECT ProductName,UnitPrice*(UnitsInStock+IFNULL(UnitsOnOrder,0))
FROM Products
or we can use the COALESCE() function, like this:
SELECT ProductName,UnitPrice*(UnitsInStock+COALESCE(UnitsOnOrder,0))
FROM Products

SQL Data Types

Data types and ranges for Microsoft Access, MySQL and SQL Server.

Microsoft Access Data Types

Data type
Description
Storage
Text
Use for text or combinations of text and numbers. 255 characters maximum

Memo
Memo is used for larger amounts of text. Stores up to 65,536 characters. Note: You cannot sort a memo field. However, they are searchable

Byte
Allows whole numbers from 0 to 255
1 byte
Integer
Allows whole numbers between -32,768 and 32,767
2 bytes
Long
Allows whole numbers between -2,147,483,648 and 2,147,483,647
4 bytes
Single
Single precision floating-point. Will handle most decimals
4 bytes
Double
Double precision floating-point. Will handle most decimals
8 bytes
Currency
Use for currency. Holds up to 15 digits of whole dollars, plus 4 decimal places. Tip: You can choose which country's currency to use
8 bytes
AutoNumber
AutoNumber fields automatically give each record its own number, usually starting at 1
4 bytes
Date/Time
Use for dates and times
8 bytes
Yes/No
A logical field can be displayed as Yes/No, True/False, or On/Off. In code, use the constants True and False (equivalent to -1 and 0). Note: Null values are not allowed in Yes/No fields
1 bit
Ole Object
Can store pictures, audio, video, or other BLOBs (Binary Large OBjects)
up to 1GB
Hyperlink
Contain links to other files, including web pages

Lookup Wizard
Let you type a list of options, which can then be chosen from a drop-down list
4 bytes

MySQL Data Types

In MySQL there are three main types : text, number, and Date/Time types.
Text types:
Data type
Description
CHAR(size)
Holds a fixed length string (can contain letters, numbers, and special characters). The fixed size is specified in parenthesis. Can store up to 255 characters
VARCHAR(size)
Holds a variable length string (can contain letters, numbers, and special characters). The maximum size is specified in parenthesis. Can store up to 255 characters. Note: If you put a greater value than 255 it will be converted to a TEXT type
TINYTEXT
Holds a string with a maximum length of 255 characters
TEXT
Holds a string with a maximum length of 65,535 characters
BLOB
For BLOBs (Binary Large OBjects). Holds up to 65,535 bytes of data
MEDIUMTEXT
Holds a string with a maximum length of 16,777,215 characters
MEDIUMBLOB
For BLOBs (Binary Large OBjects). Holds up to 16,777,215 bytes of data
LONGTEXT
Holds a string with a maximum length of 4,294,967,295 characters
LONGBLOB
For BLOBs (Binary Large OBjects). Holds up to 4,294,967,295 bytes of data
ENUM(x,y,z,etc.)
Let you enter a list of possible values. You can list up to 65535 values in an ENUM list. If a value is inserted that is not in the list, a blank value will be inserted.
Note: The values are sorted in the order you enter them.
You enter the possible values in this format: ENUM('X','Y','Z')
SET
Similar to ENUM except that SET may contain up to 64 list items and can store more than one choice
Number types:
Data type
Description
TINYINT(size)
-128 to 127 normal. 0 to 255 UNSIGNED*. The maximum number of digits may be specified in parenthesis
SMALLINT(size)
-32768 to 32767 normal. 0 to 65535 UNSIGNED*. The maximum number of digits may be specified in parenthesis
MEDIUMINT(size)
-8388608 to 8388607 normal. 0 to 16777215 UNSIGNED*. The maximum number of digits may be specified in parenthesis
INT(size)
-2147483648 to 2147483647 normal. 0 to 4294967295 UNSIGNED*. The maximum number of digits may be specified in parenthesis
BIGINT(size)
-9223372036854775808 to 9223372036854775807 normal. 0 to 18446744073709551615 UNSIGNED*. The maximum number of digits may be specified in parenthesis
FLOAT(size,d)
A small number with a floating decimal point. The maximum number of digits may be specified in the size parameter. The maximum number of digits to the right of the decimal point is specified in the d parameter
DOUBLE(size,d)
A large number with a floating decimal point. The maximum number of digits may be specified in the size parameter. The maximum number of digits to the right of the decimal point is specified in the d parameter
DECIMAL(size,d)
A DOUBLE stored as a string , allowing for a fixed decimal point. The maximum number of digits may be specified in the size parameter. The maximum number of digits to the right of the decimal point is specified in the d parameter
*The integer types have an extra option called UNSIGNED. Normally, the integer goes from an negative to positive value. Adding the UNSIGNED attribute will move that range up so it starts at zero instead of a negative number.
Date types:
Data type
Description
DATE()
A date. Format: YYYY-MM-DD
Note: The supported range is from '1000-01-01' to '9999-12-31'
DATETIME()
*A date and time combination. Format: YYYY-MM-DD HH:MM:SS
Note: The supported range is from '1000-01-01 00:00:00' to '9999-12-31 23:59:59'
TIMESTAMP()
*A timestamp. TIMESTAMP values are stored as the number of seconds since the Unix epoch ('1970-01-01 00:00:00' UTC). Format: YYYY-MM-DD HH:MM:SS
Note: The supported range is from '1970-01-01 00:00:01' UTC to '2038-01-09 03:14:07' UTC
TIME()
A time. Format: HH:MM:SS
Note: The supported range is from '-838:59:59' to '838:59:59'
YEAR()
A year in two-digit or four-digit format.
Note: Values allowed in four-digit format: 1901 to 2155. Values allowed in two-digit format: 70 to 69, representing years from 1970 to 2069
*Even if DATETIME and TIMESTAMP return the same format, they work very differently. In an INSERT or UPDATE query, the TIMESTAMP automatically set itself to the current date and time. TIMESTAMP also accepts various formats, like YYYYMMDDHHMMSS, YYMMDDHHMMSS, YYYYMMDD, or YYMMDD.

SQL Server Data Types

Character strings:
Data type
Description
Storage
char(n)
Fixed-length character string. Maximum 8,000 characters
n
varchar(n)
Variable-length character string. Maximum 8,000 characters

varchar(max)
Variable-length character string. Maximum 1,073,741,824 characters

text
Variable-length character string. Maximum 2GB of text data

Unicode strings:
Data type
Description
Storage
nchar(n)
Fixed-length Unicode data. Maximum 4,000 characters

nvarchar(n)
Variable-length Unicode data. Maximum 4,000 characters

nvarchar(max)
Variable-length Unicode data. Maximum 536,870,912 characters

ntext
Variable-length Unicode data. Maximum 2GB of text data

Binary types:
Data type
Description
Storage
bit
Allows 0, 1, or NULL

binary(n)
Fixed-length binary data. Maximum 8,000 bytes

varbinary(n)
Variable-length binary data. Maximum 8,000 bytes

varbinary(max)
Variable-length binary data. Maximum 2GB

image
Variable-length binary data. Maximum 2GB

Number types:
Data type
Description
Storage
tinyint
Allows whole numbers from 0 to 255
1 byte
smallint
Allows whole numbers between -32,768 and 32,767
2 bytes
int
Allows whole numbers between -2,147,483,648 and 2,147,483,647
4 bytes
bigint
Allows whole numbers between -9,223,372,036,854,775,808 and 9,223,372,036,854,775,807
8 bytes
decimal(p,s)
Fixed precision and scale numbers.
Allows numbers from -10^38 +1 to 10^38 –1.
The p parameter indicates the maximum total number of digits that can be stored (both to the left and to the right of the decimal point). p must be a value from 1 to 38. Default is 18.
The s parameter indicates the maximum number of digits stored to the right of the decimal point. s must be a value from 0 to p. Default value is 0
5-17 bytes
numeric(p,s)
Fixed precision and scale numbers.
Allows numbers from -10^38 +1 to 10^38 –1.
The p parameter indicates the maximum total number of digits that can be stored (both to the left and to the right of the decimal point). p must be a value from 1 to 38. Default is 18.
The s parameter indicates the maximum number of digits stored to the right of the decimal point. s must be a value from 0 to p. Default value is 0
5-17 bytes
smallmoney
Monetary data from -214,748.3648 to 214,748.3647
4 bytes
money
Monetary data from -922,337,203,685,477.5808 to 922,337,203,685,477.5807
8 bytes
float(n)
Floating precision number data from -1.79E + 308 to 1.79E + 308.
The n parameter indicates whether the field should hold 4 or 8 bytes. float(24) holds a 4-byte field and float(53) holds an 8-byte field. Default value of n is 53.
4 or 8 bytes
real
Floating precision number data from -3.40E + 38 to 3.40E + 38
4 bytes
Date types:
Data type
Description
Storage
datetime
From January 1, 1753 to December 31, 9999 with an accuracy of 3.33 milliseconds
8 bytes
datetime2
From January 1, 0001 to December 31, 9999 with an accuracy of 100 nanoseconds
6-8 bytes
smalldatetime
From January 1, 1900 to June 6, 2079 with an accuracy of 1 minute
4 bytes
date
Store a date only. From January 1, 0001 to December 31, 9999
3 bytes
time
Store a time only to an accuracy of 100 nanoseconds
3-5 bytes
datetimeoffset
The same as datetime2 with the addition of a time zone offset
8-10 bytes
timestamp
Stores a unique number that gets updated every time a row gets created or modified. The timestamp value is based upon an internal clock and does not correspond to real time. Each table may have only one timestamp variable

Other data types:
Data type
Description
sql_variant
Stores up to 8,000 bytes of data of various data types, except text, ntext, and timestamp
uniqueidentifier
Stores a globally unique identifier (GUID)
xml
Stores XML formatted data. Maximum 2GB
cursor
Stores a reference to a cursor used for database operations
table
Stores a result-set for later processing

SQL Functions

SQL has many built-in functions for performing calculations on data.

SQL Aggregate Functions

SQL aggregate functions return a single value, calculated from values in a column.
Useful aggregate functions:
·        AVG() - Returns the average value
·        COUNT() - Returns the number of rows
·        FIRST() - Returns the first value
·        LAST() - Returns the last value
·        MAX() - Returns the largest value
·        MIN() - Returns the smallest value
·        SUM() - Returns the sum

SQL Scalar functions

SQL scalar functions return a single value, based on the input value.
Useful scalar functions:
·        UCASE() - Converts a field to upper case
·        LCASE() - Converts a field to lower case
·        MID() - Extract characters from a text field
·        LEN() - Returns the length of a text field
·        ROUND() - Rounds a numeric field to the number of decimals specified
·        NOW() - Returns the current system date and time
·        FORMAT() - Formats how a field is to be displayed
Tip: The aggregate functions and the scalar functions will be explained in details in the next chapters.

SQL AVG() Function

The AVG() Function

The AVG() function returns the average value of a numeric column.

SQL AVG() Syntax

SELECT AVG(column_name) FROM table_name

SQL AVG() Example

We have the following "Orders" table:
O_Id
OrderDate
OrderPrice
Customer
1
2008/11/12
1000
Hansen
2
2008/10/23
1600
Nilsen
3
2008/09/02
700
Hansen
4
2008/09/03
300
Hansen
5
2008/08/30
2000
Jensen
6
2008/10/04
100
Nilsen
Now we want to find the average value of the "OrderPrice" fields.
We use the following SQL statement:
SELECT AVG(OrderPrice) AS OrderAverage FROM Orders
The result-set will look like this:
OrderAverage
950
Now we want to find the customers that have an OrderPrice value higher than the average OrderPrice value.
We use the following SQL statement:
SELECT Customer FROM Orders
WHERE OrderPrice>(SELECT AVG(OrderPrice) FROM Orders)
The result-set will look like this:
Customer
Hansen
Nilsen
Jensen

SQL COUNT() Function

The COUNT() function returns the number of rows that matches a specified criteria.

SQL COUNT(column_name) Syntax

The COUNT(column_name) function returns the number of values (NULL values will not be counted) of the specified column:
SELECT COUNT(column_name) FROM table_name

SQL COUNT(*) Syntax

The COUNT(*) function returns the number of records in a table:
SELECT COUNT(*) FROM table_name

SQL COUNT(DISTINCT column_name) Syntax

The COUNT(DISTINCT column_name) function returns the number of distinct values of the specified column:
SELECT COUNT(DISTINCT column_name) FROM table_name
Note: COUNT(DISTINCT) works with ORACLE and Microsoft SQL Server, but not with Microsoft Access.

SQL COUNT(column_name) Example

We have the following "Orders" table:
O_Id
OrderDate
OrderPrice
Customer
1
2008/11/12
1000
Hansen
2
2008/10/23
1600
Nilsen
3
2008/09/02
700
Hansen
4
2008/09/03
300
Hansen
5
2008/08/30
2000
Jensen
6
2008/10/04
100
Nilsen
Now we want to count the number of orders from "Customer Nilsen".
We use the following SQL statement:
SELECT COUNT(Customer) AS CustomerNilsen FROM Orders
WHERE Customer='Nilsen'
The result of the SQL statement above will be 2, because the customer Nilsen has made 2 orders in total:
CustomerNilsen
2

SQL COUNT(*) Example

If we omit the WHERE clause, like this:
SELECT COUNT(*) AS NumberOfOrders FROM Orders
The result-set will look like this:
NumberOfOrders
6
which is the total number of rows in the table.

SQL COUNT(DISTINCT column_name) Example

Now we want to count the number of unique customers in the "Orders" table.
We use the following SQL statement:
SELECT COUNT(DISTINCT Customer) AS NumberOfCustomers FROM Orders
The result-set will look like this:
NumberOfCustomers
3
which is the number of unique customers (Hansen, Nilsen, and Jensen) in the "Orders" table.

SQL FIRST() Function

The FIRST() Function

The FIRST() function returns the first value of the selected column.

SQL FIRST() Syntax

SELECT FIRST(column_name) FROM table_name

SQL FIRST() Example

We have the following "Orders" table:
O_Id
OrderDate
OrderPrice
Customer
1
2008/11/12
1000
Hansen
2
2008/10/23
1600
Nilsen
3
2008/09/02
700
Hansen
4
2008/09/03
300
Hansen
5
2008/08/30
2000
Jensen
6
2008/10/04
100
Nilsen
Now we want to find the first value of the "OrderPrice" column.
We use the following SQL statement:
SELECT FIRST(OrderPrice) AS FirstOrderPrice FROM Orders
Tip: Workaround if FIRST() function is not supported:
SELECT OrderPrice FROM Orders ORDER BY O_Id LIMIT 1
The result-set will look like this:
FirstOrderPrice
1000

SQL LAST() Function

The LAST() Function

The LAST() function returns the last value of the selected column.

SQL LAST() Syntax

SELECT LAST(column_name) FROM table_name

SQL LAST() Example

We have the following "Orders" table:
O_Id
OrderDate
OrderPrice
Customer
1
2008/11/12
1000
Hansen
2
2008/10/23
1600
Nilsen
3
2008/09/02
700
Hansen
4
2008/09/03
300
Hansen
5
2008/08/30
2000
Jensen
6
2008/10/04
100
Nilsen
Now we want to find the last value of the "OrderPrice" column.
We use the following SQL statement:
SELECT LAST(OrderPrice) AS LastOrderPrice FROM Orders
Tip: Workaround if LAST() function is not supported:
SELECT OrderPrice FROM Orders ORDER BY O_Id DESC LIMIT 1
The result-set will look like this:
LastOrderPrice
100

SQL MAX() Function

The MAX() Function

The MAX() function returns the largest value of the selected column.

SQL MAX() Syntax

SELECT MAX(column_name) FROM table_name

SQL MAX() Example

We have the following "Orders" table:
O_Id
OrderDate
OrderPrice
Customer
1
2008/11/12
1000
Hansen
2
2008/10/23
1600
Nilsen
3
2008/09/02
700
Hansen
4
2008/09/03
300
Hansen
5
2008/08/30
2000
Jensen
6
2008/10/04
100
Nilsen
Now we want to find the largest value of the "OrderPrice" column.
We use the following SQL statement:
SELECT MAX(OrderPrice) AS LargestOrderPrice FROM Orders
The result-set will look like this:
LargestOrderPrice
2000

SQL MIN() Function

The MIN() Function

The MIN() function returns the smallest value of the selected column.

SQL MIN() Syntax

SELECT MIN(column_name) FROM table_name

SQL MIN() Example

We have the following "Orders" table:
O_Id
OrderDate
OrderPrice
Customer
1
2008/11/12
1000
Hansen
2
2008/10/23
1600
Nilsen
3
2008/09/02
700
Hansen
4
2008/09/03
300
Hansen
5
2008/08/30
2000
Jensen
6
2008/10/04
100
Nilsen
Now we want to find the smallest value of the "OrderPrice" column.
We use the following SQL statement:
SELECT MIN(OrderPrice) AS SmallestOrderPrice FROM Orders
The result-set will look like this:
SmallestOrderPrice
100

SQL SUM() Function

The SUM() Function

The SUM() function returns the total sum of a numeric column.

SQL SUM() Syntax

SELECT SUM(column_name) FROM table_name

SQL SUM() Example

We have the following "Orders" table:
O_Id
OrderDate
OrderPrice
Customer
1
2008/11/12
1000
Hansen
2
2008/10/23
1600
Nilsen
3
2008/09/02
700
Hansen
4
2008/09/03
300
Hansen
5
2008/08/30
2000
Jensen
6
2008/10/04
100
Nilsen
Now we want to find the sum of all "OrderPrice" fields".
We use the following SQL statement:
SELECT SUM(OrderPrice) AS OrderTotal FROM Orders
The result-set will look like this:
OrderTotal
5700

SQL GROUP BY Statement

Aggregate functions often need an added GROUP BY statement.

The GROUP BY Statement

The GROUP BY statement is used in conjunction with the aggregate functions to group the result-set by one or more columns.

SQL GROUP BY Syntax

SELECT column_name, aggregate_function(column_name)
FROM table_name
WHERE column_name operator value
GROUP BY column_name

SQL GROUP BY Example

We have the following "Orders" table:
O_Id
OrderDate
OrderPrice
Customer
1
2008/11/12
1000
Hansen
2
2008/10/23
1600
Nilsen
3
2008/09/02
700
Hansen
4
2008/09/03
300
Hansen
5
2008/08/30
2000
Jensen
6
2008/10/04
100
Nilsen
Now we want to find the total sum (total order) of each customer.
We will have to use the GROUP BY statement to group the customers.
We use the following SQL statement:
SELECT Customer,SUM(OrderPrice) FROM Orders
GROUP BY Customer
The result-set will look like this:
Customer
SUM(OrderPrice)
Hansen
2000
Nilsen
1700
Jensen
2000
Nice! Isn't it? :)
Let's see what happens if we omit the GROUP BY statement:
SELECT Customer,SUM(OrderPrice) FROM Orders
The result-set will look like this:
Customer
SUM(OrderPrice)
Hansen
5700
Nilsen
5700
Hansen
5700
Hansen
5700
Jensen
5700
Nilsen
5700
The result-set above is not what we wanted.
Explanation of why the above SELECT statement cannot be used: The SELECT statement above has two columns specified (Customer and SUM(OrderPrice). The "SUM(OrderPrice)" returns a single value (that is the total sum of the "OrderPrice" column), while "Customer" returns 6 values (one value for each row in the "Orders" table). This will therefore not give us the correct result. However, you have seen that the GROUP BY statement solves this problem.

GROUP BY More Than One Column

We can also use the GROUP BY statement on more than one column, like this:
SELECT Customer,OrderDate,SUM(OrderPrice) FROM Orders
GROUP BY Customer,OrderDate

SQL HAVING Clause

The HAVING Clause

The HAVING clause was added to SQL because the WHERE keyword could not be used with aggregate functions.

SQL HAVING Syntax

SELECT column_name, aggregate_function(column_name)
FROM table_name
WHERE column_name operator value
GROUP BY column_name
HAVING aggregate_function(column_name) operator value

SQL HAVING Example

We have the following "Orders" table:
O_Id
OrderDate
OrderPrice
Customer
1
2008/11/12
1000
Hansen
2
2008/10/23
1600
Nilsen
3
2008/09/02
700
Hansen
4
2008/09/03
300
Hansen
5
2008/08/30
2000
Jensen
6
2008/10/04
100
Nilsen
Now we want to find if any of the customers have a total order of less than 2000.
We use the following SQL statement:
SELECT Customer,SUM(OrderPrice) FROM Orders
GROUP BY Customer
HAVING SUM(OrderPrice)<2000
The result-set will look like this:
Customer
SUM(OrderPrice)
Nilsen
1700
Now we want to find if the customers "Hansen" or "Jensen" have a total order of more than 1500.
We add an ordinary WHERE clause to the SQL statement:
SELECT Customer,SUM(OrderPrice) FROM Orders
WHERE Customer='Hansen' OR Customer='Jensen'
GROUP BY Customer
HAVING SUM(OrderPrice)>1500
The result-set will look like this:
Customer
SUM(OrderPrice)
Hansen
2000
Jensen
2000

SQL UCASE() Function

The UCASE() Function

The UCASE() function converts the value of a field to uppercase.

SQL UCASE() Syntax

SELECT UCASE(column_name) FROM table_name

Syntax for SQL Server

SELECT UPPER(column_name) FROM table_name

SQL UCASE() 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 select the content of the "LastName" and "FirstName" columns above, and convert the "LastName" column to uppercase.
We use the following SELECT statement:
SELECT UCASE(LastName) as LastName,FirstName FROM Persons
The result-set will look like this:
LastName
FirstName
HANSEN
Ola
SVENDSON
Tove
PETTERSEN
Kari

SQL LCASE() Function

The LCASE() Function

The LCASE() function converts the value of a field to lowercase.

SQL LCASE() Syntax

SELECT LCASE(column_name) FROM table_name

Syntax for SQL Server

SELECT LOWER(column_name) FROM table_name

SQL LCASE() 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 select the content of the "LastName" and "FirstName" columns above, and convert the "LastName" column to lowercase.
We use the following SELECT statement:
SELECT LCASE(LastName) as LastName,FirstName FROM Persons
The result-set will look like this:
LastName
FirstName
hansen
Ola
svendson
Tove
pettersen
Kari

SQL MID() Function

The MID() Function

The MID() function is used to extract characters from a text field.

SQL MID() Syntax

SELECT MID(column_name,start[,length]) FROM table_name

Parameter
Description
column_name
Required. The field to extract characters from
start
Required. Specifies the starting position (starts at 1)
length
Optional. The number of characters to return. If omitted, the MID() function returns the rest of the text

SQL MID() 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 extract the first four characters of the "City" column above.
We use the following SELECT statement:
SELECT MID(City,1,4) as SmallCity FROM Persons
The result-set will look like this:
SmallCity
Sand
Sand
Stav

SQL LEN() Function

The LEN() Function

The LEN() function returns the length of the value in a text field.

SQL LEN() Syntax

SELECT LEN(column_name) FROM table_name

SQL LEN() 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 select the length of the values in the "Address" column above.
We use the following SELECT statement:
SELECT LEN(Address) as LengthOfAddress FROM Persons
The result-set will look like this:
LengthOfAddress
12
9
9

SQL ROUND() Function

The ROUND() Function

The ROUND() function is used to round a numeric field to the number of decimals specified.

SQL ROUND() Syntax

SELECT ROUND(column_name,decimals) FROM table_name

Parameter
Description
column_name
Required. The field to round.
decimals
Required. Specifies the number of decimals to be returned.

SQL ROUND() Example

We have the following "Products" table:
Prod_Id
ProductName
Unit
UnitPrice
1
Jarlsberg
1000 g
10.45
2
Mascarpone
1000 g
32.56
3
Gorgonzola
1000 g
15.67
Now we want to display the product name and the price rounded to the nearest integer.
We use the following SELECT statement:
SELECT ProductName, ROUND(UnitPrice,0) as UnitPrice FROM Products
The result-set will look like this:
ProductName
UnitPrice
Jarlsberg
10
Mascarpone
33
Gorgonzola
16

SQL NOW() Function

The NOW() Function

The NOW() function returns the current system date and time.

SQL NOW() Syntax

SELECT NOW() FROM table_name

SQL NOW() Example

We have the following "Products" table:
Prod_Id
ProductName
Unit
UnitPrice
1
Jarlsberg
1000 g
10.45
2
Mascarpone
1000 g
32.56
3
Gorgonzola
1000 g
15.67
Now we want to display the products and prices per today's date.
We use the following SELECT statement:
SELECT ProductName, UnitPrice, Now() as PerDate FROM Products
The result-set will look like this:
ProductName
UnitPrice
PerDate
Jarlsberg
10.45
10/7/2008 11:25:02 AM
Mascarpone
32.56
10/7/2008 11:25:02 AM
Gorgonzola
15.67
10/7/2008 11:25:02 AM

SQL FORMAT() Function

The FORMAT() Function

The FORMAT() function is used to format how a field is to be displayed.

SQL FORMAT() Syntax

SELECT FORMAT(column_name,format) FROM table_name

Parameter
Description
column_name
Required. The field to be formatted.
format
Required. Specifies the format.

SQL FORMAT() Example

We have the following "Products" table:
Prod_Id
ProductName
Unit
UnitPrice
1
Jarlsberg
1000 g
10.45
2
Mascarpone
1000 g
32.56
3
Gorgonzola
1000 g
15.67
Now we want to display the products and prices per today's date (with today's date displayed in the following format "YYYY-MM-DD").
We use the following SELECT statement:
SELECT ProductName, UnitPrice, FORMAT(Now(),'YYYY-MM-DD') as PerDate
FROM Products
The result-set will look like this:
ProductName
UnitPrice
PerDate
Jarlsberg
10.45
2008-10-07
Mascarpone
32.56
2008-10-07
Gorgonzola
15.67
2008-10-07


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