Notes And Questions NCERT Class 12 Computer Science Chapter 11 Structured Query Language

Please refer to Structured Query Language Class 12 Computer Science Notes and important questions below. The Class 12 Computer Science Chapter wise notes have been prepared based on the latest syllabus issued for the current academic year by CBSE. Students should revise these notes and go through important Class 12 Computer Science examination questions given below to obtain better marks in exams

Structured Query Language Class 12 Computer Science Notes and Questions

The below Class 12 Structured Query Language notes have been designed by expert Computer Science teachers. These will help you a lot to understand all the important topics given in your NCERT Class 12 Computer Science textbook. Refer to Chapter 11 Structured Query Language Notes below which have been designed as per the latest syllabus issued by CBSE and will be very useful for upcoming examinations to help clear your concepts and get better marks in examinations.

♦ ORDER BY Clause: You can sort the result of a query in a specific order using ORDER BY clause. The ORDER BY clause allow sorting of query result by one or more columns. The sorting can be done either in ascending or descending order.
Note: – If order is not specified then by default the sorting will be performed in ascending order.
e.g., Select * from emp order by deptno
Three methods of ordering data are:
1. Ordering data on single column.
2. Ordering data on multiple column.
3. Ordering data on the basis of an expression
♦ Aggregate Functions: These functions operate on the multiset of values of a column of a relation, and return a value
avg: average value,
min: minimum value ,
max: maximum value ,
sum: sum of values ,
count: number of values
These functions are called aggregate functions because they operate on aggregates of tuples. The result of an aggregate function is
a single value.
e.g., Select deptno, avg (sal), sum (sal) from emp group by deptno
♦ GROUP BY Clause: The GROUP BY clause groups the rows in the result by columns that have the same values. Grouping is done on column name. It can also be performed using aggregate functions in which case the aggregate function produces single value for each group.
e.g., Select deptno, avg (sal), sum (sal) from emp group by deptno
♦ HAVING Clause: The HAVING clause place conditions on groups in contrast to WHERE clause that place conditions on individual rows. While WHERE condition cannot include aggregate functions, HAVING conditions can do so.
e.g., Select deptno, avg (sal), sum (sal) from emp group by deptno having deptno=10;
Select job, count (*) from emp group by job having count (*) <3;

Revision of MySQL:-

Field: Set of characters that represents specific data element.
Record: Collection of fields is called a record. A record can have fields of different data types.
File: Collection of similar types of records is called a file.
Table: Collection of rows and columns that contains useful data/information is called a table
Database: Collection of logically related data along with its description is termed as database.
Relation: Relation (collection of rows and columns) on which we can perform various operations. It is also known as table.
Tuple: A row in a relation is called a tuple. It is also known as record.
Attribute: A column in a relation is called an attribute. It is also termed as field or data item.
Degree: Number of attributes in a relation is called degree of a relation.
Cardinality: Number of tuples in a relation is called cardinality of a relation.
Primary Key: Primary key is a key that can uniquely identifies the records/tuples in a relation. This key can never be duplicated and NULL.
Foreign Key: Non key attribute of a table acting as primary key in some other table is known as Foreign Key in its current table. This key is used to enforce referential integrity in RDBMS.
Candidate Key: Attributes of a table which can serve as a primary key are called candidate keys.
Alternate Key: All the candidate keys other than the primary key of a relation are alternate keys for a relation.
DBA: Data Base Administrator is a person (manager) that is responsible for defining the data base schema, setting security features in database, ensuring proper functioning of the data bases etc.
Select Operation: The select operation selects tuples from a relation which satisfy a given condition. It is denoted by lowercase Greek Letter σ (sigma).
Project Operation: The project operation selects columns from a relation which satisfy a given condition. It is denoted by lowercase Greek Letter π (pi). It can be thought of as picking a sub set of all available columns.
Union Operation: The union (denoted as ∪) of a collection of relations is the set of all distinct tuples in the collection. It is a binary operation that needs two relations.
Set Difference Operation: This is denoted by – (minus) and is a binary operation. It results in a set of tuples that are in one relation but not in another

Structured Query Language

SQL is a non procedural language that is used to create, manipulate and process the databases(relations).

1. Data Definition Language (DDL)
DDL contains commands that are used to create, modify or remove the tables, databases, indexes, views,
sequences and synonyms etc.
e.g: Create table, create view, create index, alter table, drop table etc.

2. Data Manipulation Language (DML)
DML contains commands that can be used to manipulate the data base objects and to query the databases for information retrieval.
e.g: Select, Insert, Delete, and Update.

3. Transaction Control Language (TCL)
TCL include commands to control the transactions in a data base system. The commonly used commands in TCL are COMMIT,
ROLLBACK, and SAVEPOINT.

Operators in SQL: The following are the commonly used operators in SQL
1. Arithmetic Operators +,-,*, /
2. Relational Operators =, <,>, <=,>=,<>
3. Logical Operators OR, AND, NOT

Data types of SQL: Just like any other programming language, the facility of defining data of various types is available in SQL also.
Following are the most common data types of SQL.
1) NUMBER e.g. Number (n, d) Number (5, 2)
2) CHAR e.g. CHAR (SIZE)
3) VARCHAR / VARCHAR2 e.g. VARCHAR2 (SIZE)
4) DATE DD-MON-YYYY

Constraints: Constraints are the conditions that can be enforced on the attributes of a relation. The constraints come in play whenever we are trying to insert, delete or update a record in a relation.
Not null ensures that we cannot leave a column as null. That is a value has to be supplied for that column.
E.g.name varchar (25) not null
Unique constraint means that the values under that column are always unique.
E.g.Roll_no number (3) unique
Primary key constraint means that a column cannot have duplicate values and not even a null value.
e.g. Roll_no number (3) primary key
The main difference between unique and primary key constraint is that a column specified as unique may have null value but
primary key constraint does not allow null values in the column.
Foreign key is used to enforce referential integrity and is declared as a primary key in some other table.
e.g. cust_id varchar (5) references master (cust_id)
It declares cust_id column as a foreign key that refers to cust_id field of table master.
That means we cannot insert that value in cust_id filed whose corresponding value is not present in cust_id field of master
table. Moreover we can’t delete any row in master table, if a corresponding value of cust_id field is existing in the dependent table.
Check constraint limits the values that can be inserted into a column of a table.
e.g. marks number(3) check(marks>=0)
The above statement declares marks to be of type number and while inserting or updating the value in marks it is ensured that its value
is always greater than or equal to zero.
Default constraint is used to specify a default value to a column of a table automatically. This default value will be used when user does not enter any value for that column.
e.g. balance number(5)default = 0

SQL COMMANDS:
1. Create Table command is used to create a table.
The syntax of this Command is: CREATE TABLE <Table_name>
(column_name 1 data_type1 [(size) column_constraints],
column_name 1 data_type1 [(size) column_constraints],
:
[<table_constraint> (column_names)]);
2. The ALTER Table commandis used to change the definition (structure) of existing table.
ALTER TABLE <Table_name>ADD/MODIFY <Column_defnition>; For Add or modify column
ALTER TABLE <Table_name> DROP COLUMN <Column_name>; For Deleting a column
3. The INSERT Command: The rows (tuples) are added to a table by using INSERT command.
The syntax of Insert command is:
INSERT INTO <table_name> [(<column_list>)] VALUES (<value_list>);
e.g.,
INSERT INTO EMP (empno, ename, sex, sal, deptno) VALUES (1001, ’Ravi’, ’M’, 4500.00, 10);
If the order of values matches the actual order of columns in table then it is not required to give the column_list in INSERT
command. e.g.
INSERT INTO EMP VALUES (1001, ’Ravi’, ’M’, 4500.00, 10);
4. The Update command is used to change the value in a table. The syntax of this command is:
UPDATE <table_name>
SET column_name1=newvalue1/expression [, column_name2=newvalue2/expression …] WHERE <condition>;
e.g., to increase the salary of all the employees of department No 10 by 10%, then command will be:
UPDATE emp
SET sal=sal*1.1
WHERE Deptno=10;
5. The DELETE command removes rows from a table. This removes the entire rows, not individual field values.
The syntax of this command is
DELETE FROM <table_name>
[WHERE <condition>];
e.g., to delete the tuples from EMP that have salary less than 2000, the following command is used:
DELETE FROM emp WHERE sal<2000;
To delete all tuples from emp table:
DELETE FROM emp;
6. The SELECT command is used to make queries on database. A query is a command that is given to produce certain specified information from the database table(s). The SELECT command can be used to retrieve a subset of rows or columns from one or more tables. The syntax of Select Command is:
SELECT <Column-list>
FROM <table_name>
[WHERE<condition>]
[GROUP BY <column_list>]
[HAVING<condition>]
[ORDER BY <column_list [ASC|DESC]>]
The select clause list the attributes desired in the result of a query. e.g.,To
display the names of all Employees in the emp relation:
select ename from emp;
To force the elimination of duplicates, insert the keyword distinct after select. Find the
number of all departments in the emp relations, and remove duplicates
select distinct deptno from emp;
An asterisk (*) in the select clause denotes “all attributes”
SELECT* FROM emp;
The select clause can contain arithmetic expressions involving the operation, +, -, *, and /, and operating
on constants or attributes of tuples.The query:
SELECTempno, ename, sal * 12 FROM emp;
would display all values same as in the emp relation, except that the value of the attribute sal is multiplied by 12.
The WHERE clause in SELECT statement specifies the criteria for selection of rows to be returned.
• Conditions based on a range (BETWEEN Operators): The Between operator defines a range of values that the column values must fall in to make condition true. The range includes both lower value and upper value.
e.g., Find the empno of those employees whose salary between 90,000 and 100,000 (that is, 90,000 and 100,000)
SELECT empno FROM emp WHERE sal BETWEEN 90000 AND 100000;
• Conditions based on a list (IN operator): To specify a list of values, IN operator is used.
IN operator selects values that match any value in a given list of values.
For example, to display a list of members from ‘DELHI’, ‘MUMBAI’, ‘CHENNAI’ or‘BANGALORE’ cities:
SELECT * FROM members WHERE city IN (‘DELHI’, ‘MUMBAI’, ‘CHENNAI’, ‘BANGALORE’);
The NOT IN operator finds rows that do not match in the list. So if you write
SELECT * FROM members WHERE city NOT IN (‘DELHI’, ‘MUMBAI’, ‘CHENNAI’, ‘BANGALORE’);
It will list members not from the cities mentioned in the list.
• Conditions based on Pattern: SQL also includes a string-matching operator, LIKE, for comparison on character string using
patterns. Patterns are described using two special wildcard characters:
Percent (%) – ‘%’ matches any substring (one, more than one or no character).
Underscore (_) – ‘_’ character matches exactly one character.
Patterns are case-sensitive.

Like keyword is used to select row containing columns that match a wildcard pattern. The keyword not like is used to select the row that do not match the specified patterns of characters.
♦ Searching for NULL: The NULL value in a column is searched for in a table using IS NULL in the WHERE
clause (Relational Operators like =,<> etc can not be used with NULL).
For example, to list details of all employees whose departments contain NULL (i.e., novalue), you use the command:
SELECT empno, ename FROM emp Where Deptno IS NULL;
♦ The DROP Command: The DROP TABLE command is used to drop (delete) a table from database. But there is a condition for droping a table ; it must be an empty table i.e. a table with rows in it cannot be dropped.The syntax of this
command is :
DROP TABLE <Table_name>;
e.g., DROP TABLE EMP;
♦ Query Based on Two table (Join):
SELECT <Column-list>
FROM <table_name1>,<table_name2>
WHERE <Join_condition>[AND condition];