This document provides an overview of basic SQL concepts including: - The differences between DBMS and RDBMS and examples of each. - SQL and its use for managing relational databases. - Key concepts like primary keys, foreign keys, and constraints. - SQL statements for data definition, manipulation, and control. - Data types commonly used in SQL. - Basic syntax for common SQL statements like CREATE TABLE, INSERT, SELECT, and WHERE.

1. Basic SQL Presentation
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2.  DBMS and RDBMS
 SQL
 Keys
 SQL DML ,DDL , DCL Statements
 Constrains
 Cardinality
 Basic SQL coding
 Joins
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3.  DBMS stores data but not in the form of tables. i.e it does not have any tables and there
is no relationship between the data. Where as RDBMS is a Relational Data Base
Management System This adds the additional condition that the system supports a
tabular structure for the data, with enforced relationships between the tables. This
excludes the databases that don't support a tabular structure or don't enforce
relationships between tables.
 DBMS is for small organizations where RDBMS is for large amount of data and for
large Organization.
 DBMS is a single user system where as RDBMS is a multiuser system.
 DBMS does not impose any constraints or security with regard to data manipulation
where as RDNMS does.
 In DBMS there is no concept of PRIMARY KEY and FOREIGN KEY but it is included
in RDBMS. DBMS contains only flat data whereas in RDBMS there will be some
relation between the entities.
 DBMS example:- Sysbase , Foxpro
RDBMS example:- SQL Server, Oracle, MY-SQLSERVER.
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4.  SQL (Structured Query Language) is a database computer language designed for managing
data in relational database management systems (RDBMS), and originally based upon
Relational Algebra .
 To extract data from SQL server database, we use SQL coding.
 In RDBMS , data is stored in the form of Table. Table(Entity) is divided into Rows(Tuples)
and Columns(Attributes).
What is a Table
A table is a 2D representation of interrelated data, split up into columns and rows. A table is
where our data that we collect will be stored and accessed through queries.
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5. ER Relationship:- A detailed,
logical representation of the
entities, associations and data
elements for an organization or
business
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6.  Primary key: A table typically has a column or combination of columns that
contain values that uniquely identify each row in the table. This column, or
columns, is called the primary key (PK) of the table and enforces the entity
integrity of the table. When you specify a PRIMARY KEY constraint for a table,
the Database Engine enforces data uniqueness by creating a unique index for the
primary key columns.
 Foreign key: It is a field in a relational database records that point to a key field in
another table, FK implement a many-to-one relationship with another table or with
itself. Foreign keys need not to be unique within the table. The purpose of the
foreign key is to ensure referential integrity of the data. (In other words, only
values that are supposed to appear in the database are permitted.) There is no limit
on no of foreign keys on a table but recommended no is 253. A foreign key can
contain duplicate and NULL values.
 Unique key: In a table typically has a column or combination of columns that
contain values that uniquely identify each row in the table. This column, or
columns, is called as Unique key and it enforces the entity integrity of the table.
When we specify a UNIQUE KEY constraint for a table, the Database Engine
creates a unique non clustered index . It can have one NULL.
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7.  Composite Key:-A composite key is a combination of more than one column to
identify a unique row in a table
 Candidate Key :-A candidate key is one that can identify each row of a table
uniquely. Generally a candidate key becomes the primary key of the table. If the
table has more than one candidate key, one of them will become the primary key,
and the rest are called alternate keys.
 Alternate Key :- Candidate key which is not a primary key is called a Candidate
key.
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8. DDL ( Data Definition Language ) :- statements are used to define the database structure or
schema. Some examples:
 CREATE - to create objects in the database
 ALTER - alters the structure of the database
 DROP - delete objects from the database
 TRUNCATE - remove all records from a table, including all spaces allocated for the records
are removed
 COMMENT - add comments to the data dictionary
 RENAME - rename an object
DML (Data Manipulation Language ) :- statements are used for managing data within schema
objects. Some examples:
 SELECT - retrieve data from the a database
 INSERT - insert data into a table
 UPDATE - updates existing data within a table
 DELETE - deletes all records from a table, the space for the records remain
 MERGE - UPSERT operation (insert or update)
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9. DCL(Data Control Language ) is used for the control of data. That is a user can access any data
based on the privileges given to him. This is done through DATA CONTROL LANGUAGE.
Some examples:
 GRANT - gives user's access privileges to database
 REVOKE - withdraw access privileges given with the GRANT command
TCL(Transaction Control ) is used to manage the changes made by DML statements. It allows
statements to be grouped together into logical transactions. Some Example :
 COMMIT - save work done
 SAVEPOINT - identify a point in a transaction to which you can later roll back
 ROLLBACK - restore database to original since the last COMMIT
 SET TRANSACTION - Change transaction options like isolation level and what rollback
segment to use
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10. What is a Cardinality:- Relationship between the tables is called Cardinality.
What are the types of Cardinalities
 One-to-one relationships occur when there is exactly one record in the first table
that corresponds to exactly one record in the related table.
 One-to-many relationships occur when each record in Table A may have many
linked records in Table B but each record in Table B may have only one
corresponding record in Table A.
 Many-to-many relationships occur when each record in Table A may have many
linked records in Table B and vice-versa.
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12.  Varchar
 Varbinary
 Char
 Int
 Double
 Table / UniqueIdentifier / XML
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13. Cont (Data types)..
Varchar :-
 Variable length character expression, but the definition has to be defined with a
maximum length.
 Blank spaces are not stored with a varchar.
 Can be specified with MAX as the length. MAX represents a value that can be 2GB in
size
 Ex: name varchar(25)
 Char:-
 Char is fixed length of character data.
 Blank spaces are stored within a char field.
 Maximum length can be no greater than 8000.
 Binary :-
 Fixed Length binary data
 Must be specified with a maximum length value up to 8000
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14. Cont (Data types)..
Integer:-
 BigInt – 8 bytes
(+- 9,223,372,036,854,775,807)
 Int – 4 bytes (+- 2,147,483,647)
 SmallInt – 2 bytes (+- 32,767)
 TinyInt – 1 bytes (0 to 255)
DateTime
 January 1, 1753, through December 31, 9999
 8 bytes of storage
 Small datetime
 January 1, 1900, through June 6, 2079
 4 bytes of storage
 New datetime data types in 2008
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15. Syntax for “Create Table” Example:-
CREATE TABLE table_name CREATE TABLE Persons
( (
column_name1 data_type, P_Id int,
column_name2 data_type, LastName varchar(255),
column_name3 data_type, FirstName varchar(255),
.... Address varchar(255),
) City varchar(255)
)
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16. Syntax for “INSERT ”
INSERT INTO table_name
VALUES (value1, value2, value3,...)
Or
INSERT INTO table_name (column1, column2, column3,...)
VALUES (value1, value2, value3,...)
Eg:- INSERT INTO Persons
VALUES (4,'Nilsen', 'Johan', 'Bakken 2', 'Stavanger')
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17. Syntax For “Select”
SELECT column_name(s)
FROM table_name
or
SELECT * FROM table_name
Eg:- SELECT LastName,FirstName FROM Persons
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18. Syntax for “Where”
SELECT column_name(s)
FROM table_name
WHERE column_name operator value
Eg:-
SELECT * FROM Persons
WHERE City='Sandnes'
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19. Syntax for “IN” :-
SELECT column_name(s) The IN operator allows
FROM table_name you to specify multiple
WHERE column_name IN (value1,value2,...) values in a WHERE clause
Example:-
SELECT * FROM Persons
WHERE LastName IN
('Hansen','Pettersen')
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20. The AND operator displays a record if both the first condition and the second condition
is true.
The OR operator displays a record if either the first condition or the second condition is
true.
Example for “AND”:-
SELECT * FROM Persons
WHERE FirstName='Tove'
AND LastName='Svendson'
Example for “OR”:-
SELECT * FROM Persons
WHERE FirstName='Tove'
OR FirstName='Ola'
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21. The ORDER BY keyword is used to sort the result-set by a specified column. The
ORDER BY keyword sort the records in ascending order by default. If you want to
sort the records in a descending order, you can use the DESC keyword.
Syntax for “ORDER” -
SELECT column_name(s)
FROM table_name
ORDER BY column_name(s) ASC|DESC
Ex for “ORDER BY”:-
SELECT * FROM Persons
ORDER BY LastName
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22. Example for “ORDER BY”:-
SELECT * FROM Persons
ORDER BY LastName DESC
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23.  The GROUP BY statement is used in conjunction with the aggregate functions to
group the result set by one or more columns.
 Aggregate functions
◦ Sum, avg, count, min, max, bigcount
Syntax for “GROUPBY” :-
SELECT column_name, aggregate_function(column_name)
FROM table_name
WHERE column_name operator value
GROUP BY column_name
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24. Cont (Group by)
Example for “Group by” :-
SELECT Customer, SUM(OrderPrice) FROM Orders
GROUP BY Customer
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25. Cont (Group by)
EG:-
SELECT Customer, SUM(OrderPrice) FROM Orders
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.
We can use more than two columns in Group by clause
SELECT Customer, OrderDate, SUM(OrderPrice) FROM Orders
GROUP BY Customer, OrderDate
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26.  The HAVING clause was added to SQL because the WHERE keyword could not be
used with aggregate functions.
Syntax for “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
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27. Cont (Having)
Example for “Having”:-
SELECT Customer, SUM(OrderPrice)
FROM Orders
GROUP BY Customer
HAVING SUM(OrderPrice) < 2000
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28. Cont (Having)
Example for “Having” with “Where ” clause:-
SELECT Customer, SUM(OrderPrice) FROM Orders
WHERE Customer='Hansen' OR Customer='Jensen'
GROUP BY Customer
HAVING SUM(OrderPrice)>1500
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29. The UPDATE statement is used to update existing records in a table.
Syntax for “UPDATE “:-
UPDATE table_name
SET column1=value, column2=value2,...
WHERE some_column=some_value
Note: Notice the WHERE clause in the UPDATE syntax. The WHERE
clause specifies which record or records that should be updated. If you omit
the WHERE clause, all records will be updated!
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30. UPADTE Example:-
UPDATE Persons
SET Address='Nissestien 67', City='Sandnes'
WHERE LastName='Tjessem' AND FirstName='Jakob'
What happen if WHERE is not used in UPDATE
UPDATE Persons
SET Address='Nissestien 67', City='Sandnes'
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31. Syntax for “DELETE”: -
DELETE FROM table_name
WHERE some_column=some_value
The WHERE clause in the DELETE syntax. The WHERE clause specifies which
record or records that should be deleted. If you omit the WHERE clause, all records
will be deleted!
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32. Example for “Delete”:-
DELETE FROM Persons
WHERE LastName='Tjessem' AND
FirstName='Jakob'
DELETE FROM table_name
or
DELETE * FROM table_name
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33.  Sub query or the inner query or nested query is a query in a query . A sub query is
usually added in the WHERE clause of the SQL statements. Most of the times a
Sub query is used when you know how to search for a value using a SELECT
statement , but do not know the exact value.
 Sub queries are an alternate way of returning data from multiple tables.
Example :- Select id, first_name,
From student_details
Where first_name IN ( Select First_name
From Student_details
Where Subjects=„science‟);
Select product_name from product
Where product_id = (select product_id From
Order_item where item_id= 1050);
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34. JOINS
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35.  The JOIN keyword is used in an SQL statement to query data from two or more
tables, based on a relationship between certain columns in these tables.
Notice that the relationship between the two tables above is the "P_Id" column.
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36.  INNER JOIN: Return rows when there is at least one match in both tables
 LEFT JOIN: Return all rows from the left table, even if there are no matches in
the right table
 RIGHT JOIN: Return all rows from the right table, even if there are no matches in
the left table
 FULL JOIN: Return rows when there is a match in one of the tables
 SELF JOIN
 CROSS JOIN
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37. This query will return all of the records in the left table (table A) that have a
matching record in the right table (table B). This Join is written as follows:
Syntax for “Inner Join”:-
SELECT column_name(s)
FROM table_name1
INNER JOIN table_name2
ON table_name1.column_name=table_name2.column_name.
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38. Example of “Inner Join”:-
SELECT Persons.LastName, Persons.FirstName, Orders.OrderNo
FROM Persons
INNER JOIN Orders
ON Persons.P_Id=Orders.P_Id
ORDER BY Persons.LastName
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39. Cont (Inner join)
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40. will return all of the records in the left table (table A) regardless if any of those
records have a match in the right table (table B). It will also return any matching
records from the right table.
Syntax for “LEFT JOIN”:-
SELECT column_name(s)
FROM table_name1
LEFT JOIN table_name2
ON table_name1.column_name=table_name2.column_name
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41. Cont (Left Join)
In some databases LEFT JOIN is called LEFT OUTER JOIN.
Example:-
SELECT Persons.LastName, Persons.FirstName, Orders.OrderNo
FROM Persons
LEFT JOIN Orders
ON Persons.P_Id=Orders.P_Id
ORDER BY Persons.LastName
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42. SELECT Persons.LastName, Persons.FirstName, Orders.OrderNo
FROM Persons
LEFT JOIN Orders
ON Persons.P_Id=Orders.P_Id
ORDER BY Persons.LastName
The LEFT JOIN keyword returns all the rows from the left table
(Persons), even if there are no matches in the right table (Orders).
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43. This query will return all of the records in the right table (table B) regardless if
any of those records have a match in the left table (table A). It will also return any
matching records from the left table.
Syntax for “Right join” :-
SELECT column_name(s)
FROM table_name1
RIGHT JOIN table_name2
ON table_name1.column_name=table_name2.column_name
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44. Cont (right join)
Example:-
SELECT Persons.LastName, Persons.FirstName, Orders.OrderNo
FROM Persons
RIGHT JOIN Orders
ON Persons.P_Id=Orders.P_Id
ORDER BY Persons.LastName
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45. Cont (Right join)
The RIGHT JOIN keyword returns all the rows from the right table (Orders),
even if there are no matches in the left table (Persons).
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46. his Join can also be referred to as a FULL OUTER JOIN or a FULL JOIN. This query will
return all of the records from both tables, joining records from the left table (table A) that
match records from the right table (table B).
Syntax for “Full Join”:-
SELECT column_name(s)
FROM table_name1
FULL JOIN table_name2
ON table_name1.column_name=table_name2.column_name
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47. Cont (Full Join)
SELECT Persons.LastName, Persons.FirstName, Orders.OrderNo
FROM Persons
FULL JOIN Orders
ON Persons.P_Id=Orders.P_Id
ORDER BY Persons.LastName
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48. Cont (Full Join)
The FULL JOIN keyword returns all the rows from the left table (Persons), and all the
rows from the right table (Orders). If there are rows in "Persons" that do not have
matches in "Orders", or if there are rows in "Orders" that do not have matches in
"Persons", those rows will be listed as well.
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49. Left Excluding Join
This query will return all of the records in the left table
(table A) that do not match any records in the right table
(table B).
SELECT <select_list> FROM Table_A A
LEFT JOIN Table_B B ON A.Key = B.Key
WHERE B.Key IS NULL
Right Excluding join
This query will return all of the records in the right
table (table B) that do not match any records in the
left table (table A).
SELECT <select_list> FROM Table_A A RIGHT
JOIN Table_B B ON A.Key = B.Key
WHERE A.Key IS NULL
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50. Outer Excluding Join This query will return all of the records in the left
table (table A) and all of the records in the right
table (table B) that do not match. I have yet to have
a need for using this type of Join, but all of the
others,
SELECT <select_list> FROM Table_A A
FULL OUTER JOIN Table_B B
ON A.Key = B.Key
WHERE A.Key IS NULL OR B.Key IS NULL
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51.  Reference:-
 http://www.allinterview.com/showanswers/56803.html
 http://www.ntchosting.com/databases/structured-query-language.html
 http://www.excelsoftware.com/richdatamodel.html
 http://www.orafaq.com/faq/what_are_the_difference_between_ddl_dml_and_dcl_commands
 http://www.w3schools.com/sql/sql_create_table.asp
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52. NO QUESTIONS
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