Wednesday, February 11, 2015

SQL LANGUAGE- IN COMPUTER SCIENCE AND COMPUTER ENGINEERING

इस ब्लॉग्स को सृजन करने में आप सभी से सादर सुझाव आमंत्रित हैं , कृपया अपने सुझाव और प्रविष्टियाँ प्रेषित करे , इसका संपूर्ण कार्य क्षेत्र विश्व ज्ञान समुदाय हैं , जो सभी प्रतियोगियों के कॅरिअर निर्माण महत्त्वपूर्ण योगदान देगा ,आप अपने सुझाव इस मेल पत्ते पर भेज सकते हैं - chandrashekhar.malav@yahoo.com

SQL LANGUAGE- IN COMPUTER SCIENCE AND COMPUTER ENGINEERING


What is SQL?

SQL is Structured Query Language, which is a computer language for storing, manipulating and retrieving data stored in relational database.
SQL is the standard language for Relation Database System. All relational database management systems like MySQL, MS Access, Oracle, Sybase, Informix, postgres and SQL Server use SQL as standard database language.
Also, they are using different dialects, such as:
  • MS SQL Server using T-SQL,
  • Oracle using PL/SQL,
  • MS Access version of SQL is called JET SQL (native format), etc

Why SQL?

  • Allows users to access data in relational database management systems.
  • Allows users to describe the data.
  • Allows users to define the data in database and manipulate that data.
  • Allows to embed within other languages using SQL modules, libraries & pre-compilers.
  • Allows users to create and drop databases and tables.
  • Allows users to create view, stored procedure, functions in a database.
  • Allows users to set permissions on tables, procedures, and views

What is RDBMS?

RDBMS stands for Relational Database Management System. RDBMS is the basis for SQL and for all modern database systems like MS SQL Server, IBM DB2, Oracle, MySQL, and Microsoft Access.
A Relational database management system (RDBMS) is a database management system (DBMS) that is based on the relational model as introduced by E. F. Codd.

What is table ?

The data in RDBMS is stored in database objects called tables. The table is a collection of related data entries and it consists of columns and rows.
Remember, a table is the most common and simplest form of data storage in a relational database.

What is field?

Every table is broken up into smaller entities called fields. The fields in the CUSTOMERS table consist of ID, NAME, AGE, ADDRESS and SALARY.
A field is a column in a table that is designed to maintain specific information about every record in the table.

What is record or row?

A record, also called a row of data, is each individual entry that exists in a table. For example, there are 7 records in the above CUSTOMERS table.
A record is a horizontal entity in a table.

What is column?

A column is a vertical entity in a table that contains all information associated with a specific field in a table.

What is NULL value?

A NULL value in a table is a value in a field that appears to be blank which means A field with a NULL value is a field with no value.
It is very important to understand that a NULL value is different than a zero value or a field that contains spaces. A field with a NULL value is one that has been left blank during record creation.

SQL Constraints:

Constraints are the rules enforced on data columns on table. These are used to limit the type of data that can go into a table. This ensures the accuracy and reliability of the data in the database.
Constraints could be column level or table level. Column level constraints are applied only to one column where as table level constraints are applied to the whole table.

SQL Syntax:

SQL is followed by unique set of rules and guidelines called Syntax. This tutorial gives you a quick start with SQL by listing all the basic SQL Syntax:
All the SQL statements start with any of the keywords like SELECT, INSERT, UPDATE, DELETE, ALTER, DROP, CREATE, USE, SHOW and all the statements end with a semicolon (;).
Important point to be noted is that SQL is case insensitive which means SELECT and select have same meaning in SQL statements but MySQL make difference in table names. So if you are working with MySQL then you need to give table names as they exist in the database.

SQL SELECT Statement:

SELECT column1, column2....columnN
FROM   table_name;

SQL DISTINCT Clause:

SELECT DISTINCT column1, column2....columnN
FROM   table_name;

SQL WHERE Clause:

SELECT column1, column2....columnN
FROM   table_name
WHERE  CONDITION;

SQL AND/OR Clause:

SELECT column1, column2....columnN
FROM   table_name
WHERE  CONDITION-1 {AND|OR} CONDITION-2;

SQL IN Clause:

SELECT column1, column2....columnN
FROM   table_name
WHERE  column_name IN (val-1, val-2,...val-N);

SQL BETWEEN Clause:

SELECT column1, column2....columnN
FROM   table_name
WHERE  column_name BETWEEN val-1 AND val-2;

SQL Like Clause:

SELECT column1, column2....columnN
FROM   table_name
WHERE  column_name LIKE { PATTERN };

SQL ORDER BY Clause:

SELECT column1, column2....columnN
FROM   table_name
WHERE  CONDITION
ORDER BY column_name {ASC|DESC};

SQL GROUP BY Clause:

SELECT SUM(column_name)
FROM   table_name
WHERE  CONDITION
GROUP BY column_name;

SQL COUNT Clause:

SELECT COUNT(column_name)
FROM   table_name
WHERE  CONDITION;

SQL HAVING Clause:

SELECT SUM(column_name)
FROM   table_name
WHERE  CONDITION
GROUP BY column_name
HAVING (arithematic function condition);

SQL CREATE TABLE Statement:

CREATE TABLE table_name(
column1 datatype,
column2 datatype,
column3 datatype,
.....
columnN datatype,
PRIMARY KEY( one or more columns )
);

SQL DROP TABLE Statement:

DROP TABLE table_name;

SQL CREATE INDEX Statement :

CREATE UNIQUE INDEX index_name
ON table_name ( column1, column2,...columnN);

SQL DROP INDEX Statement :

ALTER TABLE table_name
DROP INDEX index_name;

SQL DESC Statement :

DESC table_name;

SQL TRUNCATE TABLE Statement:

TRUNCATE TABLE table_name;

SQL ALTER TABLE Statement:

ALTER TABLE table_name {ADD|DROP|MODIFY} column_name {data_ype};

SQL ALTER TABLE Statement (Rename) :

ALTER TABLE table_name RENAME TO new_table_name;

SQL INSERT INTO Statement:

INSERT INTO table_name( column1, column2....columnN)
VALUES ( value1, value2....valueN);

SQL UPDATE Statement:

UPDATE table_name
SET column1 = value1, column2 = value2....columnN=valueN
[ WHERE  CONDITION ];

SQL DELETE Statement:

DELETE FROM table_name
WHERE  {CONDITION};

SQL CREATE DATABASE Statement:

CREATE DATABASE database_name;

SQL DROP DATABASE Statement:

DROP DATABASE database_name;

SQL USE Statement:

USE DATABASE database_name;

SQL COMMIT Statement:

COMMIT;

SQL ROLLBACK Statement:

ROLLBACK;

SQL - Operators:

SQL Arithmetic Operators:

Assume variable a holds 10 and variable b holds 20, then:
OperatorDescriptionExample
+Addition - Adds values on either side of the operatora + b will give 30
-Subtraction - Subtracts right hand operand from left hand operanda - b will give -10
*Multiplication - Multiplies values on either side of the operatora * b will give 200
/Division - Divides left hand operand by right hand operandb / a will give 2
%Modulus - Divides left hand operand by right hand operand and returns remainderb % a will give 0

SQL Comparison Operators:

Assume variable a holds 10 and variable b holds 20, then:
OperatorDescriptionExample
=Checks if the values of two operands are equal or not, if yes then condition becomes true.(a = b) is not true.
!=Checks if the values of two operands are equal or not, if values are not equal then condition becomes true.(a != b) is true.
<>Checks if the values of two operands are equal or not, if values are not equal then condition becomes true.(a <> b) is true.
>Checks if the value of left operand is greater than the value of right operand, if yes then condition becomes true.(a > b) is not true.
<Checks if the value of left operand is less than the value of right operand, if yes then condition becomes true.(a < b) is true.
>=Checks if the value of left operand is greater than or equal to the value of right operand, if yes then condition becomes true.(a >= b) is not true.
<=Checks if the value of left operand is less than or equal to the value of right operand, if yes then condition becomes true.(a <= b) is true.
!<Checks if the value of left operand is not less than the value of right operand, if yes then condition becomes true.(a !< b) is false.
!>Checks if the value of left operand is not greater than the value of right operand, if yes then condition becomes true.(a !> b) is true.

SQL Logical Operators:

Here is a list of all the logical operators available in SQL.
OperatorDescription
ALLThe ALL operator is used to compare a value to all values in another value set.
ANDThe AND operator allows the existence of multiple conditions in an SQL statement's WHERE clause.
ANYThe ANY operator is used to compare a value to any applicable value in the list according to the condition.
BETWEENThe BETWEEN operator is used to search for values that are within a set of values, given the minimum value and the maximum value.
EXISTSThe EXISTS operator is used to search for the presence of a row in a specified table that meets certain criteria.
INThe IN operator is used to compare a value to a list of literal values that have been specified.
LIKEThe LIKE operator is used to compare a value to similar values using wildcard operators.
NOTThe NOT operator reverses the meaning of the logical operator with which it is used. Eg: NOT EXISTS, NOT BETWEEN, NOT IN, etc. This is a negate operator.
ORThe OR operator is used to combine multiple conditions in an SQL statement's WHERE clause.
IS NULLThe NULL operator is used to compare a value with a NULL value.
UNIQUEThe UNIQUE operator searches every row of a specified table for uniqueness (no duplicates).

SQL - Useful Functions:

SQL has many built-in functions for performing processing on string or numeric data. Following is the list of all useful SQL built-in functions:
  • SQL COUNT Function - The SQL COUNT aggregate function is used to count the number of rows in a database table.
  • SQL MAX Function - The SQL MAX aggregate function allows us to select the highest (maximum) value for a certain column.
  • SQL MIN Function - The SQL MIN aggregate function allows us to select the lowest (minimum) value for a certain column.
  • SQL AVG Function - The SQL AVG aggregate function selects the average value for certain table column.
  • SQL SUM Function - The SQL SUM aggregate function allows selecting the total for a numeric column.
  • SQL SQRT Functions - This is used to generate a square root of a given number.
  • SQL RAND Function - This is used to generate a random number using SQL command.
  • SQL CONCAT Function - This is used to concatenate any string inside any SQL command.
  • SQL Numeric Functions - Complete list of SQL functions required to manipulate numbers in SQL.
  • SQL String Functions - Complete list of SQL functions required to manipulate strings in SQL.
Constraints are the rules enforced on data columns on table. These are used to limit the type of data that can go into a table. This ensures the accuracy and reliability of the data in the database.
Constraints could be column level or table level. Column level constraints are applied only to one column, whereas table level constraints are applied to the whole table.
Following are commonly used constraints available in SQL. These constraints have already been discussed in SQL - RDBMS Concepts chapter but its worth to revise them at this point.
  • NOT NULL Constraint: Ensures that a column cannot have NULL value.
  • DEFAULT Constraint: Provides a default value for a column when none is specified.
  • UNIQUE Constraint: Ensures that all values in a column are different.
  • PRIMARY Key: Uniquely identified each rows/records in a database table.
  • FOREIGN Key: Uniquely identified a rows/records in any another database table.
  • CHECK Constraint: The CHECK constraint ensures that all values in a column satisfy certain conditions.
  • INDEX: Use to create and retrieve data from the database very quickly.
Constraints can be specified when a table is created with the CREATE TABLE statement or you can use ALTER TABLE statement to create constraints even after the table is created.

Dropping Constraints:

Any constraint that you have defined can be dropped using the ALTER TABLE command with the DROP CONSTRAINT option.
For example, to drop the primary key constraint in the EMPLOYEES table, you can use the following command:
ALTER TABLE EMPLOYEES DROP CONSTRAINT EMPLOYEES_PK;
Some implementations may provide shortcuts for dropping certain constraints. For example, to drop the primary key constraint for a table in Oracle, you can use the following command:
ALTER TABLE EMPLOYEES DROP PRIMARY KEY;
Some implementations allow you to disable constraints. Instead of permanently dropping a constraint from the database, you may want to temporarily disable the constraint and then enable it later.

Integrity Constraints:

Integrity constraints are used to ensure accuracy and consistency of data in a relational database. Data integrity is handled in a relational database through the concept of referential integrity.
There are many types of integrity constraints that play a role in referential integrity (RI). These constraints include Primary Key, Foreign Key, Unique Constraints and other constraints mentioned above.

The SQL Joins clause is used to combine records from two or more tables in a database. A JOIN is a means for combining fields from two tables by using values common to each.
Consider the following two tables, (a) CUSTOMERS table is as follows:
+----+----------+-----+-----------+----------+
| ID | NAME     | AGE | ADDRESS   | SALARY   |
+----+----------+-----+-----------+----------+
|  1 | Ramesh   |  32 | Ahmedabad |  2000.00 |
|  2 | Khilan   |  25 | Delhi     |  1500.00 |
|  3 | kaushik  |  23 | Kota      |  2000.00 |
|  4 | Chaitali |  25 | Mumbai    |  6500.00 |
|  5 | Hardik   |  27 | Bhopal    |  8500.00 |
|  6 | Komal    |  22 | MP        |  4500.00 |
|  7 | Muffy    |  24 | Indore    | 10000.00 |
+----+----------+-----+-----------+----------+
(b) Another table is ORDERS as follows:
+-----+---------------------+-------------+--------+
|OID  | DATE                | CUSTOMER_ID | AMOUNT |
+-----+---------------------+-------------+--------+
| 102 | 2009-10-08 00:00:00 |           3 |   3000 |
| 100 | 2009-10-08 00:00:00 |           3 |   1500 |
| 101 | 2009-11-20 00:00:00 |           2 |   1560 |
| 103 | 2008-05-20 00:00:00 |           4 |   2060 |
+-----+---------------------+-------------+--------+
Now, let us join these two tables in our SELECT statement as follows:
SQL> SELECT ID, NAME, AGE, AMOUNT
        FROM CUSTOMERS, ORDERS
        WHERE  CUSTOMERS.ID = ORDERS.CUSTOMER_ID;
This would produce the following result:
+----+----------+-----+--------+
| ID | NAME     | AGE | AMOUNT |
+----+----------+-----+--------+
|  3 | kaushik  |  23 |   3000 |
|  3 | kaushik  |  23 |   1500 |
|  2 | Khilan   |  25 |   1560 |
|  4 | Chaitali |  25 |   2060 |
+----+----------+-----+--------+
Here, it is noticeable that the join is performed in the WHERE clause. Several operators can be used to join tables, such as =, <, >, <>, <=, >=, !=, BETWEEN, LIKE, and NOT; they can all be used to join tables. However, the most common operator is the equal symbol.

SQL Join Types:

There are different types of joins available in SQL:
  • INNER JOIN: returns rows when there is a match in both tables.
  • LEFT JOIN: returns all rows from the left table, even if there are no matches in the right table.
  • RIGHT JOIN: returns all rows from the right table, even if there are no matches in the left table.
  • FULL JOIN: returns rows when there is a match in one of the tables.
  • SELF JOIN: is used to join a table to itself as if the table were two tables, temporarily renaming at least one table in the SQL statement.
  • CARTESIAN JOIN: returns the Cartesian product of the sets of records from the two or more joined tables.

The SQL UNION clause/operator is used to combine the results of two or more SELECT statements without returning any duplicate rows.
To use UNION, each SELECT must have the same number of columns selected, the same number of column expressions, the same data type, and have them in the same order, but they do not have to be the same length.

Syntax:

The basic syntax of UNION is as follows:
SELECT column1 [, column2 ]
FROM table1 [, table2 ]
[WHERE condition]

UNION

SELECT column1 [, column2 ]
FROM table1 [, table2 ]
[WHERE condition]
Here given condition could be any given expression based on your requirement.

Example:

Consider the following two tables, (a) CUSTOMERS table is as follows:
+----+----------+-----+-----------+----------+
| ID | NAME     | AGE | ADDRESS   | SALARY   |
+----+----------+-----+-----------+----------+
|  1 | Ramesh   |  32 | Ahmedabad |  2000.00 |
|  2 | Khilan   |  25 | Delhi     |  1500.00 |
|  3 | kaushik  |  23 | Kota      |  2000.00 |
|  4 | Chaitali |  25 | Mumbai    |  6500.00 |
|  5 | Hardik   |  27 | Bhopal    |  8500.00 |
|  6 | Komal    |  22 | MP        |  4500.00 |
|  7 | Muffy    |  24 | Indore    | 10000.00 |
+----+----------+-----+-----------+----------+
(b) Another table is ORDERS as follows:
+-----+---------------------+-------------+--------+
|OID  | DATE                | CUSTOMER_ID | AMOUNT |
+-----+---------------------+-------------+--------+
| 102 | 2009-10-08 00:00:00 |           3 |   3000 |
| 100 | 2009-10-08 00:00:00 |           3 |   1500 |
| 101 | 2009-11-20 00:00:00 |           2 |   1560 |
| 103 | 2008-05-20 00:00:00 |           4 |   2060 |
+-----+---------------------+-------------+--------+
Now, let us join these two tables in our SELECT statement as follows:
SQL> SELECT  ID, NAME, AMOUNT, DATE
     FROM CUSTOMERS
     LEFT JOIN ORDERS
     ON CUSTOMERS.ID = ORDERS.CUSTOMER_ID
UNION
     SELECT  ID, NAME, AMOUNT, DATE
     FROM CUSTOMERS
     RIGHT JOIN ORDERS
     ON CUSTOMERS.ID = ORDERS.CUSTOMER_ID;
This would produce the following result:
+------+----------+--------+---------------------+
| ID   | NAME     | AMOUNT | DATE                |
+------+----------+--------+---------------------+
|    1 | Ramesh   |   NULL | NULL                |
|    2 | Khilan   |   1560 | 2009-11-20 00:00:00 |
|    3 | kaushik  |   3000 | 2009-10-08 00:00:00 |
|    3 | kaushik  |   1500 | 2009-10-08 00:00:00 |
|    4 | Chaitali |   2060 | 2008-05-20 00:00:00 |
|    5 | Hardik   |   NULL | NULL                |
|    6 | Komal    |   NULL | NULL                |
|    7 | Muffy    |   NULL | NULL                |
+------+----------+--------+---------------------+

The UNION ALL Clause:

The UNION ALL operator is used to combine the results of two SELECT statements including duplicate rows.
The same rules that apply to UNION apply to the UNION ALL operator.

Syntax:

The basic syntax of UNION ALL is as follows:
SELECT column1 [, column2 ]
FROM table1 [, table2 ]
[WHERE condition]

UNION ALL

SELECT column1 [, column2 ]
FROM table1 [, table2 ]
[WHERE condition]
Here given condition could be any given expression based on your requirement.

Example:

Consider the following two tables, (a) CUSTOMERS table is as follows:
+----+----------+-----+-----------+----------+
| ID | NAME     | AGE | ADDRESS   | SALARY   |
+----+----------+-----+-----------+----------+
|  1 | Ramesh   |  32 | Ahmedabad |  2000.00 |
|  2 | Khilan   |  25 | Delhi     |  1500.00 |
|  3 | kaushik  |  23 | Kota      |  2000.00 |
|  4 | Chaitali |  25 | Mumbai    |  6500.00 |
|  5 | Hardik   |  27 | Bhopal    |  8500.00 |
|  6 | Komal    |  22 | MP        |  4500.00 |
|  7 | Muffy    |  24 | Indore    | 10000.00 |
+----+----------+-----+-----------+----------+
(b) Another table is ORDERS as follows:
+-----+---------------------+-------------+--------+
|OID  | DATE                | CUSTOMER_ID | AMOUNT |
+-----+---------------------+-------------+--------+
| 102 | 2009-10-08 00:00:00 |           3 |   3000 |
| 100 | 2009-10-08 00:00:00 |           3 |   1500 |
| 101 | 2009-11-20 00:00:00 |           2 |   1560 |
| 103 | 2008-05-20 00:00:00 |           4 |   2060 |
+-----+---------------------+-------------+--------+
Now, let us join these two tables in our SELECT statement as follows:
SQL> SELECT  ID, NAME, AMOUNT, DATE
     FROM CUSTOMERS
     LEFT JOIN ORDERS
     ON CUSTOMERS.ID = ORDERS.CUSTOMER_ID
UNION ALL
     SELECT  ID, NAME, AMOUNT, DATE
     FROM CUSTOMERS
     RIGHT JOIN ORDERS
     ON CUSTOMERS.ID = ORDERS.CUSTOMER_ID;
This would produce the following result:
+------+----------+--------+---------------------+
| ID   | NAME     | AMOUNT | DATE                |
+------+----------+--------+---------------------+
|    1 | Ramesh   |   NULL | NULL                |
|    2 | Khilan   |   1560 | 2009-11-20 00:00:00 |
|    3 | kaushik  |   3000 | 2009-10-08 00:00:00 |
|    3 | kaushik  |   1500 | 2009-10-08 00:00:00 |
|    4 | Chaitali |   2060 | 2008-05-20 00:00:00 |
|    5 | Hardik   |   NULL | NULL                |
|    6 | Komal    |   NULL | NULL                |
|    7 | Muffy    |   NULL | NULL                |
|    3 | kaushik  |   3000 | 2009-10-08 00:00:00 |
|    3 | kaushik  |   1500 | 2009-10-08 00:00:00 |
|    2 | Khilan   |   1560 | 2009-11-20 00:00:00 |
|    4 | Chaitali |   2060 | 2008-05-20 00:00:00 |
+------+----------+--------+---------------------+
There are two other clauses (i.e., operators), which are very similar to UNION clause:
  • SQL INTERSECT Clause: is used to combine two SELECT statements, but returns rows only from the first SELECT statement that are identical to a row in the second SELECT statement.
  • SQL EXCEPT Clause : combines two SELECT statements and returns rows from the first SELECT statement that are not returned by the second SELECT statement.

The SQL NULL is the term used to represent a missing value. A NULL value in a table is a value in a field that appears to be blank.
A field with a NULL value is a field with no value. It is very important to understand that a NULL value is different than a zero value or a field that contains spaces.

Syntax:

The basic syntax of NULL while creating a table:
SQL> CREATE TABLE CUSTOMERS(
   ID   INT              NOT NULL,
   NAME VARCHAR (20)     NOT NULL,
   AGE  INT              NOT NULL,
   ADDRESS  CHAR (25) ,
   SALARY   DECIMAL (18, 2),       
   PRIMARY KEY (ID)
);
Here, NOT NULL signifies that column should always accept an explicit value of the given data type. There are two columns where we did not use NOT NULL, which means these columns could be NULL.
A field with a NULL value is one that has been left blank during record creation.

Example:

The NULL value can cause problems when selecting data, however, because when comparing an unknown value to any other value, the result is always unknown and not included in the final results.
You must use the IS NULL or IS NOT NULL operators in order to check for a NULL value.
Consider the following table, CUSTOMERS having the following records:
+----+----------+-----+-----------+----------+
| ID | NAME     | AGE | ADDRESS   | SALARY   |
+----+----------+-----+-----------+----------+
|  1 | Ramesh   |  32 | Ahmedabad |  2000.00 |
|  2 | Khilan   |  25 | Delhi     |  1500.00 |
|  3 | kaushik  |  23 | Kota      |  2000.00 |
|  4 | Chaitali |  25 | Mumbai    |  6500.00 |
|  5 | Hardik   |  27 | Bhopal    |  8500.00 |
|  6 | Komal    |  22 | MP        |          |
|  7 | Muffy    |  24 | Indore    |          |
+----+----------+-----+-----------+----------+
Now, following is the usage of IS NOT NULL operator:
SQL> SELECT  ID, NAME, AGE, ADDRESS, SALARY
     FROM CUSTOMERS
     WHERE SALARY IS NOT NULL;
This would produce the following result:
+----+----------+-----+-----------+----------+
| ID | NAME     | AGE | ADDRESS   | SALARY   |
+----+----------+-----+-----------+----------+
|  1 | Ramesh   |  32 | Ahmedabad |  2000.00 |
|  2 | Khilan   |  25 | Delhi     |  1500.00 |
|  3 | kaushik  |  23 | Kota      |  2000.00 |
|  4 | Chaitali |  25 | Mumbai    |  6500.00 |
|  5 | Hardik   |  27 | Bhopal    |  8500.00 |
+----+----------+-----+-----------+----------+
Now, following is the usage of IS NULL operator:
SQL> SELECT  ID, NAME, AGE, ADDRESS, SALARY
     FROM CUSTOMERS
     WHERE SALARY IS NULL;
This would produce the following result:
+----+----------+-----+-----------+----------+
| ID | NAME     | AGE | ADDRESS   | SALARY   |
+----+----------+-----+-----------+----------+
|  6 | Komal    |  22 | MP        |          |
|  7 | Muffy    |  24 | Indore    |          |
+----+----------+-----+-----------+----------+

You can rename a table or a column temporarily by giving another name known as alias.



The use of table aliases means to rename a table in a particular SQL statement. The renaming is a temporary change and the actual table name does not change in the database.



The column aliases are used to rename a table's columns for the purpose of a particular SQL query.



Syntax:



The basic syntax of table alias is as follows:


SELECT column1, column2....
FROM table_name AS alias_name
WHERE [condition];



The basic syntax of column alias is as follows:


SELECT column_name AS alias_name
FROM table_name
WHERE [condition];



Example:



Consider the following two tables, (a) CUSTOMERS table is as follows:


+----+----------+-----+-----------+----------+
| ID | NAME     | AGE | ADDRESS   | SALARY   |
+----+----------+-----+-----------+----------+
|  1 | Ramesh   |  32 | Ahmedabad |  2000.00 |
|  2 | Khilan   |  25 | Delhi     |  1500.00 |
|  3 | kaushik  |  23 | Kota      |  2000.00 |
|  4 | Chaitali |  25 | Mumbai    |  6500.00 |
|  5 | Hardik   |  27 | Bhopal    |  8500.00 |
|  6 | Komal    |  22 | MP        |  4500.00 |
|  7 | Muffy    |  24 | Indore    | 10000.00 |
+----+----------+-----+-----------+----------+



(b) Another table is ORDERS as follows:


+-----+---------------------+-------------+--------+
|OID  | DATE                | CUSTOMER_ID | AMOUNT |
+-----+---------------------+-------------+--------+
| 102 | 2009-10-08 00:00:00 |           3 |   3000 |
| 100 | 2009-10-08 00:00:00 |           3 |   1500 |
| 101 | 2009-11-20 00:00:00 |           2 |   1560 |
| 103 | 2008-05-20 00:00:00 |           4 |   2060 |
+-----+---------------------+-------------+--------+



Now, following is the usage of table alias:


SQL> SELECT C.ID, C.NAME, C.AGE, O.AMOUNT 
        FROM CUSTOMERS AS C, ORDERS AS O
        WHERE  C.ID = O.CUSTOMER_ID;



This would produce the following result:


+----+----------+-----+--------+
| ID | NAME     | AGE | AMOUNT |
+----+----------+-----+--------+
|  3 | kaushik  |  23 |   3000 |
|  3 | kaushik  |  23 |   1500 |
|  2 | Khilan   |  25 |   1560 |
|  4 | Chaitali |  25 |   2060 |
+----+----------+-----+--------+



Following is the usage of column alias:


SQL> SELECT  ID AS CUSTOMER_ID, NAME AS CUSTOMER_NAME
     FROM CUSTOMERS
     WHERE SALARY IS NOT NULL;



This would produce the following result:


+-------------+---------------+
| CUSTOMER_ID | CUSTOMER_NAME |
+-------------+---------------+
|           1 | Ramesh        |
|           2 | Khilan        |
|           3 | kaushik       |
|           4 | Chaitali      |
|           5 | Hardik        |
|           6 | Komal         |
|           7 | Muffy         |

Indexes are special lookup tables that the database search engine can use to speed up data retrieval. Simply put, an index is a pointer to data in a table. An index in a database is very similar to an index in the back of a book.
For example, if you want to reference all pages in a book that discuss a certain topic, you first refer to the index, which lists all topics alphabetically and are then referred to one or more specific page numbers.
An index helps speed up SELECT queries and WHERE clauses, but it slows down data input, with UPDATE and INSERT statements. Indexes can be created or dropped with no effect on the data.
Creating an index involves the CREATE INDEX statement, which allows you to name the index, to specify the table and which column or columns to index, and to indicate whether the index is in ascending or descending order.
Indexes can also be unique, similar to the UNIQUE constraint, in that the index prevents duplicate entries in the column or combination of columns on which there's an index.

The CREATE INDEX Command:

The basic syntax of CREATE INDEX is as follows:
CREATE INDEX index_name ON table_name;

Single-Column Indexes:

A single-column index is one that is created based on only one table column. The basic syntax is as follows:
CREATE INDEX index_name
ON table_name (column_name);

Unique Indexes:

Unique indexes are used not only for performance, but also for data integrity. A unique index does not allow any duplicate values to be inserted into the table. The basic syntax is as follows:
CREATE UNIQUE INDEX index_name
on table_name (column_name);

Composite Indexes:

A composite index is an index on two or more columns of a table. The basic syntax is as follows:
CREATE INDEX index_name
on table_name (column1, column2);
Whether to create a single-column index or a composite index, take into consideration the column(s) that you may use very frequently in a query's WHERE clause as filter conditions.
Should there be only one column used, a single-column index should be the choice. Should there be two or more columns that are frequently used in the WHERE clause as filters, the composite index would be the best choice.

Implicit Indexes:

Implicit indexes are indexes that are automatically created by the database server when an object is created. Indexes are automatically created for primary key constraints and unique constraints.

The DROP INDEX Command:

An index can be dropped using SQL DROP command. Care should be taken when dropping an index because performance may be slowed or improved.
The basic syntax is as follows:
DROP INDEX index_name;
You can check INDEX Constraint chapter to see actual examples on Indexes.

When should indexes be avoided?

Although indexes are intended to enhance a database's performance, there are times when they should be avoided. The following guidelines indicate when the use of an index should be reconsidered:
  • Indexes should not be used on small tables.
  • Tables that have frequent, large batch update or insert operations.
  • Indexes should not be used on columns that contain a high number of NULL values.
  • Columns that are frequently manipulated should not be indexed.

The SQL ALTER TABLE command is used to add, delete or modify columns in an existing table.
You would also use ALTER TABLE command to add and drop various constraints on a an existing table.

Syntax:

The basic syntax of ALTER TABLE to add a new column in an existing table is as follows:
ALTER TABLE table_name ADD column_name datatype;
The basic syntax of ALTER TABLE to DROP COLUMN in an existing table is as follows:
ALTER TABLE table_name DROP COLUMN column_name;
The basic syntax of ALTER TABLE to change the DATA TYPE of a column in a table is as follows:
ALTER TABLE table_name MODIFY COLUMN column_name datatype;
The basic syntax of ALTER TABLE to add a NOT NULL constraint to a column in a table is as follows:
ALTER TABLE table_name MODIFY column_name datatype NOT NULL;
The basic syntax of ALTER TABLE to ADD UNIQUE CONSTRAINT to a table is as follows:
ALTER TABLE table_name 
ADD CONSTRAINT MyUniqueConstraint UNIQUE(column1, column2...);
The basic syntax of ALTER TABLE to ADD CHECK CONSTRAINT to a table is as follows:
ALTER TABLE table_name 
ADD CONSTRAINT MyUniqueConstraint CHECK (CONDITION);
The basic syntax of ALTER TABLE to ADD PRIMARY KEY constraint to a table is as follows:
ALTER TABLE table_name 
ADD CONSTRAINT MyPrimaryKey PRIMARY KEY (column1, column2...);
The basic syntax of ALTER TABLE to DROP CONSTRAINT from a table is as follows:
ALTER TABLE table_name 
DROP CONSTRAINT MyUniqueConstraint;
If you're using MySQL, the code is as follows:
ALTER TABLE table_name 
DROP INDEX MyUniqueConstraint;
The basic syntax of ALTER TABLE to DROP PRIMARY KEY constraint from a table is as follows:
ALTER TABLE table_name 
DROP CONSTRAINT MyPrimaryKey;
If you're using MySQL, the code is as follows:
ALTER TABLE table_name 
DROP PRIMARY KEY;

Example:

Consider the CUSTOMERS table having the following records:
+----+----------+-----+-----------+----------+
| ID | NAME     | AGE | ADDRESS   | SALARY   |
+----+----------+-----+-----------+----------+
|  1 | Ramesh   |  32 | Ahmedabad |  2000.00 |
|  2 | Khilan   |  25 | Delhi     |  1500.00 |
|  3 | kaushik  |  23 | Kota      |  2000.00 |
|  4 | Chaitali |  25 | Mumbai    |  6500.00 |
|  5 | Hardik   |  27 | Bhopal    |  8500.00 |
|  6 | Komal    |  22 | MP        |  4500.00 |
|  7 | Muffy    |  24 | Indore    | 10000.00 |
+----+----------+-----+-----------+----------+
Following is the example to ADD a new column in an existing table:
ALTER TABLE CUSTOMERS ADD SEX char(1);
Now, CUSTOMERS table is changed and following would be output from SELECT statement:
+----+---------+-----+-----------+----------+------+
| ID | NAME    | AGE | ADDRESS   | SALARY   | SEX  |
+----+---------+-----+-----------+----------+------+
|  1 | Ramesh  |  32 | Ahmedabad |  2000.00 | NULL |
|  2 | Ramesh  |  25 | Delhi     |  1500.00 | NULL |
|  3 | kaushik |  23 | Kota      |  2000.00 | NULL |
|  4 | kaushik |  25 | Mumbai    |  6500.00 | NULL |
|  5 | Hardik  |  27 | Bhopal    |  8500.00 | NULL |
|  6 | Komal   |  22 | MP        |  4500.00 | NULL |
|  7 | Muffy   |  24 | Indore    | 10000.00 | NULL |
+----+---------+-----+-----------+----------+------+
Following is the example to DROP sex column from existing table:
ALTER TABLE CUSTOMERS DROP SEX;
Now, CUSTOMERS table is changed and following would be output from SELECT statement:
+----+---------+-----+-----------+----------+
| ID | NAME    | AGE | ADDRESS   | SALARY   |
+----+---------+-----+-----------+----------+
|  1 | Ramesh  |  32 | Ahmedabad |  2000.00 |
|  2 | Ramesh  |  25 | Delhi     |  1500.00 |
|  3 | kaushik |  23 | Kota      |  2000.00 |
|  4 | kaushik |  25 | Mumbai    |  6500.00 |
|  5 | Hardik  |  27 | Bhopal    |  8500.00 |
|  6 | Komal   |  22 | MP        |  4500.00 |
|  7 | Muffy   |  24 | Indore    | 10000.00 |
+----+---------+-----+-----------+----------+



The SQL TRUNCATE TABLE command is used to delete complete data from an existing table.



You can also use DROP TABLE command to delete complete table but it would remove complete table structure form the database and you would need to re-create this table once again if you wish you store some data.



Syntax:



The basic syntax of TRUNCATE TABLE is as follows:


TRUNCATE TABLE  table_name;



Example:



Consider the CUSTOMERS table having the following records:


+----+----------+-----+-----------+----------+
| ID | NAME     | AGE | ADDRESS   | SALARY   |
+----+----------+-----+-----------+----------+
|  1 | Ramesh   |  32 | Ahmedabad |  2000.00 |
|  2 | Khilan   |  25 | Delhi     |  1500.00 |
|  3 | kaushik  |  23 | Kota      |  2000.00 |
|  4 | Chaitali |  25 | Mumbai    |  6500.00 |
|  5 | Hardik   |  27 | Bhopal    |  8500.00 |
|  6 | Komal    |  22 | MP        |  4500.00 |
|  7 | Muffy    |  24 | Indore    | 10000.00 |
+----+----------+-----+-----------+----------+



Following is the example to truncate:


SQL > TRUNCATE TABLE CUSTOMERS;



Now, CUSTOMERS table is truncated and following would be the output from SELECT statement:


SQL> SELECT * FROM CUSTOMERS;
Empty set (0.00 sec)



A view is nothing more than a SQL statement that is stored in the database with an associated name. A view is actually a composition of a table in the form of a predefined SQL query.



A view can contain all rows of a table or select rows from a table. A view can be created from one or many tables which depends on the written SQL query to create a view.



Views, which are kind of virtual tables, allow users to do the following:


    

  • 
Structure data in a way that users or classes of users find natural or intuitive.
    

    • 

  • 
Restrict access to the data such that a user can see and (sometimes) modify exactly what they need and no more.
    

    • 

  • 
Summarize data from various tables which can be used to generate reports.
    

    • 




Creating Views:



Database views are created using the CREATE VIEW statement. Views can be created from a single table, multiple tables, or another view.



To create a view, a user must have the appropriate system privilege according to the specific implementation.



The basic CREATE VIEW syntax is as follows:


CREATE VIEW view_name AS
SELECT column1, column2.....
FROM table_name
WHERE [condition];



You can include multiple tables in your SELECT statement in very similar way as you use them in normal SQL SELECT query.



Example:



Consider the CUSTOMERS table having the following records:


+----+----------+-----+-----------+----------+
| ID | NAME     | AGE | ADDRESS   | SALARY   |
+----+----------+-----+-----------+----------+
|  1 | Ramesh   |  32 | Ahmedabad |  2000.00 |
|  2 | Khilan   |  25 | Delhi     |  1500.00 |
|  3 | kaushik  |  23 | Kota      |  2000.00 |
|  4 | Chaitali |  25 | Mumbai    |  6500.00 |
|  5 | Hardik   |  27 | Bhopal    |  8500.00 |
|  6 | Komal    |  22 | MP        |  4500.00 |
|  7 | Muffy    |  24 | Indore    | 10000.00 |
+----+----------+-----+-----------+----------+



Now, following is the example to create a view from CUSTOMERS table. This view would be used to have customer name and age from CUSTOMERS table:


SQL > CREATE VIEW CUSTOMERS_VIEW AS
SELECT name, age
FROM  CUSTOMERS;



Now, you can query CUSTOMERS_VIEW in similar way as you query an actual table. Following is the example:


SQL > SELECT * FROM CUSTOMERS_VIEW;



This would produce the following result:


+----------+-----+
| name     | age |
+----------+-----+
| Ramesh   |  32 |
| Khilan   |  25 |
| kaushik  |  23 |
| Chaitali |  25 |
| Hardik   |  27 |
| Komal    |  22 |
| Muffy    |  24 |
+----------+-----+



The WITH CHECK OPTION:



The WITH CHECK OPTION is a CREATE VIEW statement option. The purpose of the WITH CHECK OPTION is to ensure that all UPDATE and INSERTs satisfy the condition(s) in the view definition.



If they do not satisfy the condition(s), the UPDATE or INSERT returns an error.



The following is an example of creating same view CUSTOMERS_VIEW with the WITH CHECK OPTION:


CREATE VIEW CUSTOMERS_VIEW AS
SELECT name, age
FROM  CUSTOMERS
WHERE age IS NOT NULL
WITH CHECK OPTION;



The WITH CHECK OPTION in this case should deny the entry of any NULL values in the view's AGE column, because the view is defined by data that does not have a NULL value in the AGE column.



Updating a View:



A view can be updated under certain conditions:


    

  • 
The SELECT clause may not contain the keyword DISTINCT.
    

    • 

  • 
The SELECT clause may not contain summary functions.
    

    • 

  • 
The SELECT clause may not contain set functions.
    

    • 

  • 
The SELECT clause may not contain set operators.
    

    • 

  • 
The SELECT clause may not contain an ORDER BY clause.
    

    • 

  • 
The FROM clause may not contain multiple tables.
    

    • 

  • 
The WHERE clause may not contain subqueries.
    

    • 

  • 
The query may not contain GROUP BY or HAVING.
    

    • 

  • 
Calculated columns may not be updated.
    

    • 

  • 
All NOT NULL columns from the base table must be included in the view in order for the INSERT query to function.
    

    • 




So if a view satisfies all the above-mentioned rules then you can update a view. Following is an example to update the age of Ramesh:


SQL > UPDATE CUSTOMERS_VIEW
      SET AGE = 35
      WHERE name='Ramesh';



This would ultimately update the base table CUSTOMERS and same would reflect in the view itself. Now, try to query base table, and SELECT statement would produce the following result:


+----+----------+-----+-----------+----------+
| ID | NAME     | AGE | ADDRESS   | SALARY   |
+----+----------+-----+-----------+----------+
|  1 | Ramesh   |  35 | Ahmedabad |  2000.00 |
|  2 | Khilan   |  25 | Delhi     |  1500.00 |
|  3 | kaushik  |  23 | Kota      |  2000.00 |
|  4 | Chaitali |  25 | Mumbai    |  6500.00 |
|  5 | Hardik   |  27 | Bhopal    |  8500.00 |
|  6 | Komal    |  22 | MP        |  4500.00 |
|  7 | Muffy    |  24 | Indore    | 10000.00 |
+----+----------+-----+-----------+----------+



Inserting Rows into a View:



Rows of data can be inserted into a view. The same rules that apply to the UPDATE command also apply to the INSERT command.



Here we can not insert rows in CUSTOMERS_VIEW because we have not included all the NOT NULL columns in this view, otherwise you can insert rows in a view in similar way as you insert them in a table.



Deleting Rows into a View:



Rows of data can be deleted from a view. The same rules that apply to the UPDATE and INSERT commands apply to the DELETE command.



Following is an example to delete a record having AGE= 22.


SQL > DELETE FROM CUSTOMERS_VIEW
      WHERE age = 22;



This would ultimately delete a row from the base table CUSTOMERS and same would reflect in the view itself. Now, try to query base table, and SELECT statement would produce the following result:


+----+----------+-----+-----------+----------+
| ID | NAME     | AGE | ADDRESS   | SALARY   |
+----+----------+-----+-----------+----------+
|  1 | Ramesh   |  35 | Ahmedabad |  2000.00 |
|  2 | Khilan   |  25 | Delhi     |  1500.00 |
|  3 | kaushik  |  23 | Kota      |  2000.00 |
|  4 | Chaitali |  25 | Mumbai    |  6500.00 |
|  5 | Hardik   |  27 | Bhopal    |  8500.00 |
|  7 | Muffy    |  24 | Indore    | 10000.00 |
+----+----------+-----+-----------+----------+



Dropping Views:



Obviously, where you have a view, you need a way to drop the view if it is no longer needed. The syntax is very simple as given below:


DROP VIEW view_name;



Following is an example to drop CUSTOMERS_VIEW from CUSTOMERS table:


DROP VIEW CUSTOMERS_VIEW;







The HAVING clause enables you to specify conditions that filter which group results appear in the final results.



The WHERE clause places conditions on the selected columns, whereas the HAVING clause places conditions on groups created by the GROUP BY clause.



Syntax:



The following is the position of the HAVING clause in a query:


SELECT
FROM
WHERE
GROUP BY
HAVING
ORDER BY



The HAVING clause must follow the GROUP BY clause in a query and must also precede the ORDER BY clause if used. The following is the syntax of the SELECT statement, including the HAVING clause:


SELECT column1, column2
FROM table1, table2
WHERE [ conditions ]
GROUP BY column1, column2
HAVING [ conditions ]
ORDER BY column1, column2



Example:



Consider the CUSTOMERS table having the following records:


+----+----------+-----+-----------+----------+
| ID | NAME     | AGE | ADDRESS   | SALARY   |
+----+----------+-----+-----------+----------+
|  1 | Ramesh   |  32 | Ahmedabad |  2000.00 |
|  2 | Khilan   |  25 | Delhi     |  1500.00 |
|  3 | kaushik  |  23 | Kota      |  2000.00 |
|  4 | Chaitali |  25 | Mumbai    |  6500.00 |
|  5 | Hardik   |  27 | Bhopal    |  8500.00 |
|  6 | Komal    |  22 | MP        |  4500.00 |
|  7 | Muffy    |  24 | Indore    | 10000.00 |
+----+----------+-----+-----------+----------+



Following is the example, which would display record for which similar age count would be more than or equal to 2:


SQL > SELECT ID, NAME, AGE, ADDRESS, SALARY
FROM CUSTOMERS
GROUP BY age
HAVING COUNT(age) >= 2;



This would produce the following result:


+----+--------+-----+---------+---------+
| ID | NAME   | AGE | ADDRESS | SALARY  |
+----+--------+-----+---------+---------+
|  2 | Khilan |  25 | Delhi   | 1500.00 |



A transaction is a unit of work that is performed against a database. Transactions are units or sequences of work accomplished in a logical order, whether in a manual fashion by a user or automatically by some sort of a database program.



A transaction is the propagation of one or more changes to the database. For example, if you are creating a record or updating a record or deleting a record from the table, then you are performing transaction on the table. It is important to control transactions to ensure data integrity and to handle database errors.



Practically, you will club many SQL queries into a group and you will execute all of them together as a part of a transaction.



Properties of Transactions:



Transactions have the following four standard properties, usually referred to by the acronym ACID:


    

  • 
Atomicity: ensures that all operations within the work unit are completed successfully; otherwise, the transaction is aborted at the point of failure, and previous operations are rolled back to their former state.
    

    • 

  • 
Consistency: ensures that the database properly changes states upon a successfully committed transaction.
    

    • 

  • 
Isolation: enables transactions to operate independently of and transparent to each other.
    

    • 

  • 
Durability: ensures that the result or effect of a committed transaction persists in case of a system failure.
    

    • 




Transaction Control:



There are following commands used to control transactions:


    

  • 
COMMIT: to save the changes.
    

    • 

  • 
ROLLBACK: to rollback the changes.
    

    • 

  • 
SAVEPOINT: creates points within groups of transactions in which to ROLLBACK
    

    • 

  • 
SET TRANSACTION: Places a name on a transaction.
    

    • 




Transactional control commands are only used with the DML commands INSERT, UPDATE and DELETE only. They can not be used while creating tables or dropping them because these operations are automatically commited in the database.



The COMMIT Command:



The COMMIT command is the transactional command used to save changes invoked by a transaction to the database.



The COMMIT command saves all transactions to the database since the last COMMIT or ROLLBACK command.



The syntax for COMMIT command is as follows:


COMMIT;



Example:



Consider the CUSTOMERS table having the following records:


+----+----------+-----+-----------+----------+
| ID | NAME     | AGE | ADDRESS   | SALARY   |
+----+----------+-----+-----------+----------+
|  1 | Ramesh   |  32 | Ahmedabad |  2000.00 |
|  2 | Khilan   |  25 | Delhi     |  1500.00 |
|  3 | kaushik  |  23 | Kota      |  2000.00 |
|  4 | Chaitali |  25 | Mumbai    |  6500.00 |
|  5 | Hardik   |  27 | Bhopal    |  8500.00 |
|  6 | Komal    |  22 | MP        |  4500.00 |
|  7 | Muffy    |  24 | Indore    | 10000.00 |
+----+----------+-----+-----------+----------+



Following is the example which would delete records from the table having age = 25 and then COMMIT the changes in the database.


SQL> DELETE FROM CUSTOMERS
     WHERE AGE = 25;
SQL> COMMIT;



As a result, two rows from the table would be deleted and SELECT statement would produce the following result:


+----+----------+-----+-----------+----------+
| ID | NAME     | AGE | ADDRESS   | SALARY   |
+----+----------+-----+-----------+----------+
|  1 | Ramesh   |  32 | Ahmedabad |  2000.00 |
|  3 | kaushik  |  23 | Kota      |  2000.00 |
|  5 | Hardik   |  27 | Bhopal    |  8500.00 |
|  6 | Komal    |  22 | MP        |  4500.00 |
|  7 | Muffy    |  24 | Indore    | 10000.00 |
+----+----------+-----+-----------+----------+



The ROLLBACK Command:



The ROLLBACK command is the transactional command used to undo transactions that have not already been saved to the database.



The ROLLBACK command can only be used to undo transactions since the last COMMIT or ROLLBACK command was issued.



The syntax for ROLLBACK command is as follows:


ROLLBACK;



Example:



Consider the CUSTOMERS table having the following records:


+----+----------+-----+-----------+----------+
| ID | NAME     | AGE | ADDRESS   | SALARY   |
+----+----------+-----+-----------+----------+
|  1 | Ramesh   |  32 | Ahmedabad |  2000.00 |
|  2 | Khilan   |  25 | Delhi     |  1500.00 |
|  3 | kaushik  |  23 | Kota      |  2000.00 |
|  4 | Chaitali |  25 | Mumbai    |  6500.00 |
|  5 | Hardik   |  27 | Bhopal    |  8500.00 |
|  6 | Komal    |  22 | MP        |  4500.00 |
|  7 | Muffy    |  24 | Indore    | 10000.00 |
+----+----------+-----+-----------+----------+



Following is the example, which would delete records from the table having age = 25 and then ROLLBACK the changes in the database.


SQL> DELETE FROM CUSTOMERS
     WHERE AGE = 25;
SQL> ROLLBACK;



As a result, delete operation would not impact the table and SELECT statement would produce the following result:


+----+----------+-----+-----------+----------+
| ID | NAME     | AGE | ADDRESS   | SALARY   |
+----+----------+-----+-----------+----------+
|  1 | Ramesh   |  32 | Ahmedabad |  2000.00 |
|  2 | Khilan   |  25 | Delhi     |  1500.00 |
|  3 | kaushik  |  23 | Kota      |  2000.00 |
|  4 | Chaitali |  25 | Mumbai    |  6500.00 |
|  5 | Hardik   |  27 | Bhopal    |  8500.00 |
|  6 | Komal    |  22 | MP        |  4500.00 |
|  7 | Muffy    |  24 | Indore    | 10000.00 |
+----+----------+-----+-----------+----------+



The SAVEPOINT Command:



A SAVEPOINT is a point in a transaction when you can roll the transaction back to a certain point without rolling back the entire transaction.



The syntax for SAVEPOINT command is as follows:


SAVEPOINT SAVEPOINT_NAME;



This command serves only in the creation of a SAVEPOINT among transactional statements. The ROLLBACK command is used to undo a group of transactions.



The syntax for rolling back to a SAVEPOINT is as follows:


ROLLBACK TO SAVEPOINT_NAME;



Following is an example where you plan to delete the three different records from the CUSTOMERS table. You want to create a SAVEPOINT before each delete, so that you can ROLLBACK to any SAVEPOINT at any time to return the appropriate data to its original state:



Example:



Consider the CUSTOMERS table having the following records:


+----+----------+-----+-----------+----------+
| ID | NAME     | AGE | ADDRESS   | SALARY   |
+----+----------+-----+-----------+----------+
|  1 | Ramesh   |  32 | Ahmedabad |  2000.00 |
|  2 | Khilan   |  25 | Delhi     |  1500.00 |
|  3 | kaushik  |  23 | Kota      |  2000.00 |
|  4 | Chaitali |  25 | Mumbai    |  6500.00 |
|  5 | Hardik   |  27 | Bhopal    |  8500.00 |
|  6 | Komal    |  22 | MP        |  4500.00 |
|  7 | Muffy    |  24 | Indore    | 10000.00 |
+----+----------+-----+-----------+----------+



Now, here is the series of operations:


SQL> SAVEPOINT SP1;
Savepoint created.
SQL> DELETE FROM CUSTOMERS WHERE ID=1;
1 row deleted.
SQL> SAVEPOINT SP2;
Savepoint created.
SQL> DELETE FROM CUSTOMERS WHERE ID=2;
1 row deleted.
SQL> SAVEPOINT SP3;
Savepoint created.
SQL> DELETE FROM CUSTOMERS WHERE ID=3;
1 row deleted.



Now that the three deletions have taken place, say you have changed your mind and decided to ROLLBACK to the SAVEPOINT that you identified as SP2. Because SP2 was created after the first deletion, the last two deletions are undone:


SQL> ROLLBACK TO SP2;
Rollback complete.



Notice that only the first deletion took place since you rolled back to SP2:


SQL> SELECT * FROM CUSTOMERS;
+----+----------+-----+-----------+----------+
| ID | NAME     | AGE | ADDRESS   | SALARY   |
+----+----------+-----+-----------+----------+
|  2 | Khilan   |  25 | Delhi     |  1500.00 |
|  3 | kaushik  |  23 | Kota      |  2000.00 |
|  4 | Chaitali |  25 | Mumbai    |  6500.00 |
|  5 | Hardik   |  27 | Bhopal    |  8500.00 |
|  6 | Komal    |  22 | MP        |  4500.00 |
|  7 | Muffy    |  24 | Indore    | 10000.00 |
+----+----------+-----+-----------+----------+
6 rows selected.



The RELEASE SAVEPOINT Command:



The RELEASE SAVEPOINT command is used to remove a SAVEPOINT that you have created.



The syntax for RELEASE SAVEPOINT is as follows:


RELEASE SAVEPOINT SAVEPOINT_NAME;



Once a SAVEPOINT has been released, you can no longer use the ROLLBACK command to undo transactions performed since the SAVEPOINT.



The SET TRANSACTION Command:



The SET TRANSACTION command can be used to initiate a database transaction. This command is used to specify characteristics for the transaction that follows.



For example, you can specify a transaction to be read only, or read write.



The syntax for SET TRANSACTION is as follows:


SET TRANSACTION [ READ WRITE | READ ONLY ];







SEE SQL LANGUAGES IN FULL TEXT IN PDF
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