DevOps

Wednesday, 4 December 2013

SQL Tutorials 3

SQL Data Types

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 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
12008/11/121000Hansen
22008/10/231600Nilsen
32008/09/02700Hansen
42008/09/03300Hansen
52008/08/302000Jensen
62008/10/04100Nilsen
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
12008/11/121000Hansen
22008/10/231600Nilsen
32008/09/02700Hansen
42008/09/03300Hansen
52008/08/302000Jensen
62008/10/04100Nilsen
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
12008/11/121000Hansen
22008/10/231600Nilsen
32008/09/02700Hansen
42008/09/03300Hansen
52008/08/302000Jensen
62008/10/04100Nilsen
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
Note 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
12008/11/121000Hansen
22008/10/231600Nilsen
32008/09/02700Hansen
42008/09/03300Hansen
52008/08/302000Jensen
62008/10/04100Nilsen
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
Note 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
12008/11/121000Hansen
22008/10/231600Nilsen
32008/09/02700Hansen
42008/09/03300Hansen
52008/08/302000Jensen
62008/10/04100Nilsen
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
12008/11/121000Hansen
22008/10/231600Nilsen
32008/09/02700Hansen
42008/09/03300Hansen
52008/08/302000Jensen
62008/10/04100Nilsen
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
12008/11/121000Hansen
22008/10/231600Nilsen
32008/09/02700Hansen
42008/09/03300Hansen
52008/08/302000Jensen
62008/10/04100Nilsen
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
12008/11/121000Hansen
22008/10/231600Nilsen
32008/09/02700Hansen
42008/09/03300Hansen
52008/08/302000Jensen
62008/10/04100Nilsen
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)
Hansen2000
Nilsen1700
Jensen2000
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)
Hansen5700
Nilsen5700
Hansen5700
Hansen5700
Jensen5700
Nilsen5700
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
12008/11/121000Hansen
22008/10/231600Nilsen
32008/09/02700Hansen
42008/09/03300Hansen
52008/08/302000Jensen
62008/10/04100Nilsen
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)
Nilsen1700
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)
Hansen2000
Jensen2000



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
1HansenOlaTimoteivn 10Sandnes
2SvendsonToveBorgvn 23Sandnes
3PettersenKariStorgt 20Stavanger
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
HANSENOla
SVENDSONTove
PETTERSENKari



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
1HansenOlaTimoteivn 10Sandnes
2SvendsonToveBorgvn 23Sandnes
3PettersenKariStorgt 20Stavanger
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
hansenOla
svendsonTove
pettersenKari



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_nameRequired. The field to extract characters from
startRequired. Specifies the starting position (starts at 1)
lengthOptional. 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
1HansenOlaTimoteivn 10Sandnes
2SvendsonToveBorgvn 23Sandnes
3PettersenKariStorgt 20Stavanger
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
1HansenOlaTimoteivn 10Sandnes
2SvendsonToveBorgvn 23Sandnes
3PettersenKariStorgt 20Stavanger
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_nameRequired. The field to round.
decimalsRequired. Specifies the number of decimals to be returned.

SQL ROUND() Example

We have the following "Products" table:
Prod_Id
ProductName
Unit
UnitPrice
1Jarlsberg1000 g10.45
2Mascarpone1000 g32.56
3Gorgonzola1000 g15.67
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
Jarlsberg10
Mascarpone33
Gorgonzola16




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
1Jarlsberg1000 g10.45
2Mascarpone1000 g32.56
3Gorgonzola1000 g15.67
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
Jarlsberg10.4510/7/2008 11:25:02 AM
Mascarpone32.5610/7/2008 11:25:02 AM
Gorgonzola15.6710/7/2008 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_nameRequired. The field to be formatted.
formatRequired. Specifies the format.

SQL FORMAT() Example

We have the following "Products" table:
Prod_Id
ProductName
Unit
UnitPrice
1Jarlsberg1000 g10.45
2Mascarpone1000 g32.56
3Gorgonzola1000 g15.67
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
Jarlsberg10.452008-10-07
Mascarpone32.562008-10-07
Gorgonzola15.672008-10-07



SQL Quick Reference From W3Schools




SQL Statement
Syntax
AND / OR
SELECT column_name(s)
FROM table_name
WHERE condition
AND|OR condition
ALTER TABLE
ALTER TABLE table_name
ADD column_name datatype
or
ALTER TABLE table_name
DROP COLUMN column_name
AS (alias)
SELECT column_name AS column_alias
FROM table_name
or
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 TABLE
CREATE TABLE table_name
(
column_name1 data_type,
column_name2 data_type,
column_name2 data_type,
...
)
CREATE INDEX
CREATE INDEX index_name
ON table_name (column_name)
or
CREATE UNIQUE INDEX index_name
ON table_name (column_name)
CREATE VIEW
CREATE VIEW view_name AS
SELECT column_name(s)
FROM table_name
WHERE condition
DELETE
DELETE FROM table_name
WHERE some_column=some_value
or
DELETE FROM table_name
(Note: Deletes the entire table!!)
DELETE * FROM table_name
(Note: Deletes the entire table!!)
DROP DATABASE
DROP DATABASE database_name
DROP INDEX
DROP INDEX table_name.index_name (SQL Server)
DROP INDEX index_name ON table_name (MS Access)
DROP INDEX index_name (DB2/Oracle)
ALTER TABLE table_name
DROP INDEX index_name (MySQL)
DROP TABLE
DROP TABLE table_name
GROUP BY
SELECT column_name, aggregate_function(column_name)
FROM table_name
WHERE column_name operator value
GROUP BY column_name
HAVING
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
IN
SELECT column_name(s)
FROM table_name
WHERE column_name
IN (value1,value2,..)
INSERT INTO
INSERT INTO table_name
VALUES (value1, value2, value3,....)
or
INSERT INTO table_name
(column1, column2, column3,...)
VALUES (value1, value2, value3,....)
INNER JOIN
SELECT column_name(s)
FROM table_name1
INNER JOIN table_name2
ON table_name1.column_name=table_name2.column_name
LEFT JOIN
SELECT column_name(s)
FROM table_name1
LEFT JOIN table_name2
ON table_name1.column_name=table_name2.column_name
RIGHT JOIN
SELECT column_name(s)
FROM table_name1
RIGHT JOIN table_name2
ON table_name1.column_name=table_name2.column_name
FULL JOIN
SELECT column_name(s)
FROM table_name1
FULL JOIN table_name2
ON table_name1.column_name=table_name2.column_name
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
SELECT *
INTO new_table_name [IN externaldatabase]
FROM old_table_name
or
SELECT column_name(s)
INTO new_table_name [IN externaldatabase]
FROM old_table_name
SELECT TOP
SELECT TOP number|percent column_name(s)
FROM table_name
TRUNCATE TABLE
TRUNCATE TABLE table_name
UNION
SELECT column_name(s) FROM table_name1
UNION
SELECT column_name(s) FROM table_name2
UNION ALL
SELECT column_name(s) FROM table_name1
UNION ALL
SELECT column_name(s) FROM table_name2
UPDATE
UPDATE table_name
SET column1=value, column2=value,...
WHERE some_column=some_value
WHERE
SELECT column_name(s)
FROM table_name
WHERE column_name operator value




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