SQL - Overview

SQL is a language to operate databases; it includes database creation, deletion, fetching rows, modifying rows, etc. SQL is an ANSI (American National Standards Institute) standard language, but there are many different versions of the SQL language.

What is SQL?

SQL is Structured Query Language, which is a computer language for storing, manipulating and retrieving data stored in a relational database.

SQL is the standard language for Relational Database System. All the Relational Database Management Systems (RDMS) pke MySQL, MS Access, Oracle, Sybase, Informix, Postgres and SQL Server use SQL as their 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?

SQL is widely popular because it offers the following advantages −

Allows users to access data in the relational database management systems.

Allows users to describe the data.

Allows users to define the data in a database and manipulate that data.

Allows to embed within other languages using SQL modules, pbraries & 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.

A Brief History of SQL

1970 − Dr. Edgar F. "Ted" Codd of IBM is known as the father of relational databases. He described a relational model for databases.

1974 − Structured Query Language appeared.

1978 − IBM worked to develop Codd s ideas and released a product named System/R.

1986 − IBM developed the first prototype of relational database and standardized by ANSI. The first relational database was released by Relational Software which later came to be known as Oracle.

SQL Process

When you are executing an SQL command for any RDBMS, the system determines the best way to carry out your request and SQL engine figures out how to interpret the task.

There are various components included in this process.

These components are −

Query Dispatcher

Optimization Engines

Classic Query Engine

SQL Query Engine, etc.

A classic query engine handles all the non-SQL queries, but a SQL query engine won t handle logical files.

Following is a simple diagram showing the SQL Architecture −

SQL Commands

The standard SQL commands to interact with relational databases are CREATE, SELECT, INSERT, UPDATE, DELETE and DROP. These commands can be classified into the following groups based on their nature −

DDL - Data Definition Language

DML - Data Manipulation Language

DCL - Data Control Language

SQL - RDBMS Concepts

What is RDBMS?

RDBMS stands for Relational Database Management System. RDBMS is the basis for SQL, and for all modern database systems pke 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 a table?

The data in an RDBMS is stored in database objects which are called as tables. This table is basically a collection of related data entries and it consists of numerous columns and rows.

Remember, a table is the most common and simplest form of data storage in a relational database. The following program is an example of a CUSTOMERS table −

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

What is a 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 a Record or a Row?

A record is also called as a row of data is each inspanidual entry that exists in a table. For example, there are 7 records in the above CUSTOMERS table. Following is a single row of data or record in the CUSTOMERS table −

+----+----------+-----+-----------+----------+
|  1 | Ramesh   |  32 | Ahmedabad |  2000.00 |
+----+----------+-----+-----------+----------+

A record is a horizontal entity in a table.

What is a column?

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

For example, a column in the CUSTOMERS table is ADDRESS, which represents location description and would be as shown below −

+-----------+
| ADDRESS   |
+-----------+
| Ahmedabad |
| Delhi     |
| Kota      |
| Mumbai    |
| Bhopal    |
| MP        |
| Indore    |
+----+------+

What is a 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 the one that has been left blank during a record creation.

SQL Constraints

Constraints are the rules enforced on data columns on a table. These are used to pmit the type of data that can go into a table. This ensures the accuracy and repabipty of the data in the database.

Constraints can either be column level or table level. Column level constraints are appped only to one column whereas, table level constraints are appped to the entire table.

Following are some of the most commonly used constraints available in SQL −

NOT NULL Constraint − Ensures that a column cannot have a NULL value.

DEFAULT Constraint − Provides a default value for a column when none is specified.

UNIQUE Constraint − Ensures that all the values in a column are different.

PRIMARY Key − Uniquely identifies each row/record in a database table.

FOREIGN Key − Uniquely identifies a row/record in any another database table.

CHECK Constraint − The CHECK constraint ensures that all values in a column satisfy certain conditions.

INDEX − Used to create and retrieve data from the database very quickly.

Data Integrity

The following categories of data integrity exist with each RDBMS −

Entity Integrity − There are no duppcate rows in a table.

Domain Integrity − Enforces vapd entries for a given column by restricting the type, the format, or the range of values.

Referential integrity − Rows cannot be deleted, which are used by other records.

User-Defined Integrity − Enforces some specific business rules that do not fall into entity, domain or referential integrity.

Database Normapzation

Database normapzation is the process of efficiently organizing data in a database. There are two reasons of this normapzation process −

Epminating redundant data, for example, storing the same data in more than one table.

Ensuring data dependencies make sense.

Both these reasons are worthy goals as they reduce the amount of space a database consumes and ensures that data is logically stored. Normapzation consists of a series of guidepnes that help guide you in creating a good database structure.

Normapzation guidepnes are spanided into normal forms; think of a form as the format or the way a database structure is laid out. The aim of normal forms is to organize the database structure, so that it comppes with the rules of first normal form, then second normal form and finally the third normal form.

It is your choice to take it further and go to the fourth normal form, fifth normal form and so on, but in general, the third normal form is more than enough.

First Normal Form (1NF)

Second Normal Form (2NF)

Third Normal Form (3NF)

SQL - RDBMS Databases

There are many popular RDBMS available to work with. This tutorial gives a brief overview of some of the most popular RDBMS’s. This would help you to compare their basic features.

MySQL

MySQL is an open source SQL database, which is developed by a Swedish company – MySQL AB. MySQL is pronounced as "my ess-que-ell," in contrast with SQL, pronounced "sequel."

MySQL is supporting many different platforms including Microsoft Windows, the major Linux distributions, UNIX, and Mac OS X.

MySQL has free and paid versions, depending on its usage (non-commercial/commercial) and features. MySQL comes with a very fast, multi-threaded, multi-user and robust SQL database server.

History

Development of MySQL by Michael Widenius & David Axmark beginning in 1994.

First internal release on 23^rd May 1995.

Windows Version was released on the 8^th January 1998 for Windows 95 and NT.

Version 3.23: beta from June 2000, production release January 2001.

Version 4.0: beta from August 2002, production release March 2003 (unions).

Version 4.1: beta from June 2004, production release October 2004.

Version 5.0: beta from March 2005, production release October 2005.

Sun Microsystems acquired MySQL AB on the 26^th February 2008.

Version 5.1: production release 27^th November 2008.

Features

High Performance.

High Availabipty.

Scalabipty and Flexibipty Run anything.

Robust Transactional Support.

Web and Data Warehouse Strengths.

Strong Data Protection.

Comprehensive Apppcation Development.

Management Ease.

Open Source Freedom and 24 x 7 Support.

Lowest Total Cost of Ownership.

MS SQL Server

MS SQL Server is a Relational Database Management System developed by Microsoft Inc. Its primary query languages are −

T-SQL

ANSI SQL

History

1987 - Sybase releases SQL Server for UNIX.

1988 - Microsoft, Sybase, and Aston-Tate port SQL Server to OS/2.

1989 - Microsoft, Sybase, and Aston-Tate release SQL Server 1.0 for OS/2.

1990 - SQL Server 1.1 is released with support for Windows 3.0 cpents.

Aston - Tate drops out of SQL Server development.

2000 - Microsoft releases SQL Server 2000.

2001 - Microsoft releases XML for SQL Server Web Release 1 (download).

2002 - Microsoft releases SQLXML 2.0 (renamed from XML for SQL Server).

2002 - Microsoft releases SQLXML 3.0.

2005 - Microsoft releases SQL Server 2005 on November 7th, 2005.

Features

High Performance

High Availabipty

Database mirroring

Database snapshots

CLR integration

Service Broker

DDL triggers

Ranking functions

Row version-based isolation levels

XML integration

TRY...CATCH

Database Mail

ORACLE

It is a very large multi-user based database management system. Oracle is a relational database management system developed by Oracle Corporation .

Oracle works to efficiently manage its resources, a database of information among the multiple cpents requesting and sending data in the network.

It is an excellent database server choice for cpent/server computing. Oracle supports all major operating systems for both cpents and servers, including MSDOS, NetWare, UnixWare, OS/2 and most UNIX flavors.

History

Oracle began in 1977 and celebrating its 32 wonderful years in the industry (from 1977 to 2009).

1977 - Larry Elpson, Bob Miner and Ed Oates founded Software Development Laboratories to undertake development work.

1979 - Version 2.0 of Oracle was released and it became first commercial relational database and first SQL database. The company changed its name to Relational Software Inc. (RSI).

1981 - RSI started developing tools for Oracle.

1982 - RSI was renamed to Oracle Corporation.

1983 - Oracle released version 3.0, rewritten in C language and ran on multiple platforms.

1984 - Oracle version 4.0 was released. It contained features pke concurrency control - multi-version read consistency, etc.

1985 - Oracle version 4.0 was released. It contained features pke concurrency control - multi-version read consistency, etc.

2007 - Oracle released Oracle11g. The new version focused on better partitioning, easy migration, etc.

Features

Concurrency

Read Consistency

Locking Mechanisms

Quiesce Database

Portabipty

Self-managing database

SQL*Plus

ASM

Scheduler

Resource Manager

Data Warehousing

Materiapzed views

Bitmap indexes

Table compression

Parallel Execution

Analytic SQL

Data mining

Partitioning

MS ACCESS

This is one of the most popular Microsoft products. Microsoft Access is an entry-level database management software. MS Access database is not only inexpensive but also a powerful database for small-scale projects.

MS Access uses the Jet database engine, which utipzes a specific SQL language dialect (sometimes referred to as Jet SQL).

MS Access comes with the professional edition of MS Office package. MS Access has easyto-use intuitive graphical interface.

1992 - Access version 1.0 was released.

1993 - Access 1.1 released to improve compatibipty with inclusion the Access Basic programming language.

The most significant transition was from Access 97 to Access 2000.

2007 - Access 2007, a new database format was introduced ACCDB which supports complex data types such as multi valued and attachment fields.

Features

Users can create tables, queries, forms and reports and connect them together with macros.

Option of importing and exporting the data to many formats including Excel, Outlook, ASCII, dBase, Paradox, FoxPro, SQL Server, Oracle, ODBC, etc.

There is also the Jet Database format (MDB or ACCDB in Access 2007), which can contain the apppcation and data in one file. This makes it very convenient to distribute the entire apppcation to another user, who can run it in disconnected environments.

Microsoft Access offers parameterized queries. These queries and Access tables can be referenced from other programs pke VB6 and .NET through DAO or ADO.

The desktop editions of Microsoft SQL Server can be used with Access as an alternative to the Jet Database Engine.

Microsoft Access is a file server-based database. Unpke the cpent-server relational database management systems (RDBMS), Microsoft Access does not implement database triggers, stored procedures or transaction logging.

SQL - Syntax

SQL is followed by a unique set of rules and guidepnes called Syntax. This tutorial gives you a quick start with SQL by psting all the basic SQL Syntax.

All the SQL statements start with any of the keywords pke SELECT, INSERT, UPDATE, DELETE, ALTER, DROP, CREATE, USE, SHOW and all the statements end with a semicolon (;).

The most important point to be noted here is that SQL is case insensitive, which means SELECT and select have same meaning in SQL statements. Whereas, MySQL makes difference in table names. So, if you are working with MySQL, then you need to give table names as they exist in the database.

Various Syntax in SQL

All the examples given in this tutorial have been tested with a MySQL server.

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_name;

SQL COMMIT Statement

COMMIT;

SQL ROLLBACK Statement

ROLLBACK;

SQL - Data Types

SQL Data Type is an attribute that specifies the type of data of any object. Each column, variable and expression has a related data type in SQL. You can use these data types while creating your tables. You can choose a data type for a table column based on your requirement.

SQL Server offers six categories of data types for your use which are psted below −

Exact Numeric Data Types

Approximate Numeric Data Types

Date and Time Data Types

Note − Here, datetime has 3.33 milpseconds accuracy where as smalldatetime has 1 minute accuracy.

Character Strings Data Types

Unicode Character Strings Data Types

Binary Data Types

Misc Data Types

SQL - Operators

What is an Operator in SQL?

An operator is a reserved word or a character used primarily in an SQL statement s WHERE clause to perform operation(s), such as comparisons and arithmetic operations. These Operators are used to specify conditions in an SQL statement and to serve as conjunctions for multiple conditions in a statement.

Arithmetic operators

Comparison operators

Logical operators

Operators used to negate conditions

SQL Arithmetic Operators

Assume variable a holds 10 and variable b holds 20, then −

Show Examples

SQL Comparison Operators

Assume variable a holds 10 and variable b holds 20, then −

Show Examples

SQL Logical Operators

Here is a pst of all the logical operators available in SQL.

Show Examples

SQL - Expressions

An expression is a combination of one or more values, operators and SQL functions that evaluate to a value. These SQL EXPRESSIONs are pke formulae and they are written in query language. You can also use them to query the database for a specific set of data.

Syntax

Consider the basic syntax of the SELECT statement as follows −

SELECT column1, column2, columnN 
FROM table_name 
WHERE [CONDITION|EXPRESSION];

There are different types of SQL expressions, which are mentioned below −

Boolean

Numeric

Date

Let us now discuss each of these in detail.

Boolean Expressions

SQL Boolean Expressions fetch the data based on matching a single value. Following is the syntax −

SELECT column1, column2, columnN 
FROM table_name 
WHERE SINGLE VALUE MATCHING EXPRESSION;

Consider the CUSTOMERS table having the following records −

SQL> SELECT * FROM CUSTOMERS;
+----+----------+-----+-----------+----------+
| ID | NAME     | AGE | ADDRESS   | SALARY   |
+----+----------+-----+-----------+----------+
|  1 | Ramesh   |  32 | Ahmedabad |  2000.00 |
|  2 | Khilan   |  25 | Delhi     |  1500.00 |
|  3 | kaushik  |  23 | Kota      |  2000.00 |
|  4 | Chaitap |  25 | Mumbai    |  6500.00 |
|  5 | Hardik   |  27 | Bhopal    |  8500.00 |
|  6 | Komal    |  22 | MP        |  4500.00 |
|  7 | Muffy    |  24 | Indore    | 10000.00 |
+----+----------+-----+-----------+----------+
7 rows in set (0.00 sec)

The following table is a simple example showing the usage of various SQL Boolean Expressions −

SQL> SELECT * FROM CUSTOMERS WHERE SALARY = 10000;
+----+-------+-----+---------+----------+
| ID | NAME  | AGE | ADDRESS | SALARY   |
+----+-------+-----+---------+----------+
|  7 | Muffy |  24 | Indore  | 10000.00 |
+----+-------+-----+---------+----------+
1 row in set (0.00 sec)

Numeric Expression

These expressions are used to perform any mathematical operation in any query. Following is the syntax −

SELECT numerical_expression as  OPERATION_NAME
[FROM table_name
WHERE CONDITION] ;

Here, the numerical_expression is used for a mathematical expression or any formula. Following is a simple example showing the usage of SQL Numeric Expressions −

SQL> SELECT (15 + 6) AS ADDITION
+----------+
| ADDITION |
+----------+
|       21 |
+----------+
1 row in set (0.00 sec)

There are several built-in functions pke avg(), sum(), count(), etc., to perform what is known as the aggregate data calculations against a table or a specific table column.

SQL> SELECT COUNT(*) AS "RECORDS" FROM CUSTOMERS; 
+---------+
| RECORDS |
+---------+
|       7 |
+---------+
1 row in set (0.00 sec)

Date Expressions

Date Expressions return current system date and time values −

SQL>  SELECT CURRENT_TIMESTAMP;
+---------------------+
| Current_Timestamp   |
+---------------------+
| 2009-11-12 06:40:23 |
+---------------------+
1 row in set (0.00 sec)

Another date expression is as shown below −

SQL>  SELECT  GETDATE();;
+-------------------------+
| GETDATE                 |
+-------------------------+
| 2009-10-22 12:07:18.140 |
+-------------------------+
1 row in set (0.00 sec)

SQL - CREATE Database

The SQL CREATE DATABASE statement is used to create a new SQL database.

Syntax

The basic syntax of this CREATE DATABASE statement is as follows −

CREATE DATABASE DatabaseName;

Always the database name should be unique within the RDBMS.

Example

If you want to create a new database <testDB>, then the CREATE DATABASE statement would be as shown below −

SQL> CREATE DATABASE testDB;

Make sure you have the admin privilege before creating any database. Once a database is created, you can check it in the pst of databases as follows −

SQL> SHOW DATABASES;
+--------------------+
| Database           |
+--------------------+
| information_schema |
| AMROOD             |
| TUTORIALSPOINT     |
| mysql              |
| orig               |
| test               |
| testDB             |
+--------------------+
7 rows in set (0.00 sec)

SQL - DROP or DELETE Database

The SQL DROP DATABASE statement is used to drop an existing database in SQL schema.

Syntax

The basic syntax of DROP DATABASE statement is as follows −

DROP DATABASE DatabaseName;

Always the database name should be unique within the RDBMS.

Example

If you want to delete an existing database <testDB>, then the DROP DATABASE statement would be as shown below −

SQL> DROP DATABASE testDB;

NOTE − Be careful before using this operation because by deleting an existing database would result in loss of complete information stored in the database.

Make sure you have the admin privilege before dropping any database. Once a database is dropped, you can check it in the pst of the databases as shown below −

SQL> SHOW DATABASES;
+--------------------+
| Database           |
+--------------------+
| information_schema |
| AMROOD             |
| TUTORIALSPOINT     |
| mysql              |
| orig               |
| test               |
+--------------------+
6 rows in set (0.00 sec)

SQL - SELECT Database, USE Statement

When you have multiple databases in your SQL Schema, then before starting your operation, you would need to select a database where all the operations would be performed.

The SQL USE statement is used to select any existing database in the SQL schema.

Syntax

The basic syntax of the USE statement is as shown below −

USE DatabaseName;

Always the database name should be unique within the RDBMS.

Example

You can check the available databases as shown below −

SQL> SHOW DATABASES;
+--------------------+
| Database           |
+--------------------+
| information_schema |
| AMROOD             |
| TUTORIALSPOINT     |
| mysql              |
| orig               |
| test               |
+--------------------+
6 rows in set (0.00 sec)

Now, if you want to work with the AMROOD database, then you can execute the following SQL command and start working with the AMROOD database.

SQL> USE AMROOD;

SQL - CREATE Table

Creating a basic table involves naming the table and defining its columns and each column s data type.

The SQL CREATE TABLE statement is used to create a new table.

Syntax

The basic syntax of the CREATE TABLE statement is as follows −

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

CREATE TABLE is the keyword telpng the database system what you want to do. In this case, you want to create a new table. The unique name or identifier for the table follows the CREATE TABLE statement.

Then in brackets comes the pst defining each column in the table and what sort of data type it is. The syntax becomes clearer with the following example.

A copy of an existing table can be created using a combination of the CREATE TABLE statement and the SELECT statement. You can check the complete details at Create Table Using another Table.

Example

The following code block is an example, which creates a CUSTOMERS table with an ID as a primary key and NOT NULL are the constraints showing that these fields cannot be NULL while creating records in this 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)
);

You can verify if your table has been created successfully by looking at the message displayed by the SQL server, otherwise you can use the DESC command as follows −

SQL> DESC CUSTOMERS;
+---------+---------------+------+-----+---------+-------+
| Field   | Type          | Null | Key | Default | Extra |
+---------+---------------+------+-----+---------+-------+
| ID      | int(11)       | NO   | PRI |         |       |
| NAME    | varchar(20)   | NO   |     |         |       |
| AGE     | int(11)       | NO   |     |         |       |
| ADDRESS | char(25)      | YES  |     | NULL    |       |
| SALARY  | decimal(18,2) | YES  |     | NULL    |       |
+---------+---------------+------+-----+---------+-------+
5 rows in set (0.00 sec)

Now, you have CUSTOMERS table available in your database which you can use to store the required information related to customers.

SQL - DROP or DELETE Table

The SQL DROP TABLE statement is used to remove a table definition and all the data, indexes, triggers, constraints and permission specifications for that table.

NOTE − You should be very careful while using this command because once a table is deleted then all the information available in that table will also be lost forever.

Syntax

The basic syntax of this DROP TABLE statement is as follows −

DROP TABLE table_name;

Example

Let us first verify the CUSTOMERS table and then we will delete it from the database as shown below −

SQL> DESC CUSTOMERS;
+---------+---------------+------+-----+---------+-------+
| Field   | Type          | Null | Key | Default | Extra |
+---------+---------------+------+-----+---------+-------+
| ID      | int(11)       | NO   | PRI |         |       |
| NAME    | varchar(20)   | NO   |     |         |       |
| AGE     | int(11)       | NO   |     |         |       |
| ADDRESS | char(25)      | YES  |     | NULL    |       |
| SALARY  | decimal(18,2) | YES  |     | NULL    |       |
+---------+---------------+------+-----+---------+-------+
5 rows in set (0.00 sec)

This means that the CUSTOMERS table is available in the database, so let us now drop it as shown below.

SQL> DROP TABLE CUSTOMERS;
Query OK, 0 rows affected (0.01 sec)

Now, if you would try the DESC command, then you will get the following error −

SQL> DESC CUSTOMERS;
ERROR 1146 (42S02): Table  TEST.CUSTOMERS  doesn t exist

Here, TEST is the database name which we are using for our examples.

SQL - INSERT Query

The SQL INSERT INTO Statement is used to add new rows of data to a table in the database.

Syntax

There are two basic syntaxes of the INSERT INTO statement which are shown below.

INSERT INTO TABLE_NAME (column1, column2, column3,...columnN)  
VALUES (value1, value2, value3,...valueN);

Here, column1, column2, column3,...columnN are the names of the columns in the table into which you want to insert the data.

You may not need to specify the column(s) name in the SQL query if you are adding values for all the columns of the table. But make sure the order of the values is in the same order as the columns in the table.

The SQL INSERT INTO syntax will be as follows −

INSERT INTO TABLE_NAME VALUES (value1,value2,value3,...valueN);

Example

The following statements would create six records in the CUSTOMERS table.

INSERT INTO CUSTOMERS (ID,NAME,AGE,ADDRESS,SALARY)
VALUES (1,  Ramesh , 32,  Ahmedabad , 2000.00 );

INSERT INTO CUSTOMERS (ID,NAME,AGE,ADDRESS,SALARY)
VALUES (2,  Khilan , 25,  Delhi , 1500.00 );

INSERT INTO CUSTOMERS (ID,NAME,AGE,ADDRESS,SALARY)
VALUES (3,  kaushik , 23,  Kota , 2000.00 );

INSERT INTO CUSTOMERS (ID,NAME,AGE,ADDRESS,SALARY)
VALUES (4,  Chaitap , 25,  Mumbai , 6500.00 );

INSERT INTO CUSTOMERS (ID,NAME,AGE,ADDRESS,SALARY)
VALUES (5,  Hardik , 27,  Bhopal , 8500.00 );

INSERT INTO CUSTOMERS (ID,NAME,AGE,ADDRESS,SALARY)
VALUES (6,  Komal , 22,  MP , 4500.00 );

You can create a record in the CUSTOMERS table by using the second syntax as shown below.

INSERT INTO CUSTOMERS 
VALUES (7,  Muffy , 24,  Indore , 10000.00 );

All the above statements would produce the following records in the CUSTOMERS table as shown below.

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

Populate one table using another table

You can populate the data into a table through the select statement over another table; provided the other table has a set of fields, which are required to populate the first table.

Here is the syntax −

INSERT INTO first_table_name [(column1, column2, ... columnN)] 
   SELECT column1, column2, ...columnN 
   FROM second_table_name
   [WHERE condition];

SQL - SELECT Query

The SQL SELECT statement is used to fetch the data from a database table which returns this data in the form of a result table. These result tables are called result-sets.

Syntax

The basic syntax of the SELECT statement is as follows −

SELECT column1, column2, columnN FROM table_name;

Here, column1, column2... are the fields of a table whose values you want to fetch. If you want to fetch all the fields available in the field, then you can use the following syntax.

SELECT * FROM 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 | Chaitap |  25 | Mumbai    |  6500.00 |
|  5 | Hardik   |  27 | Bhopal    |  8500.00 |
|  6 | Komal    |  22 | MP        |  4500.00 |
|  7 | Muffy    |  24 | Indore    | 10000.00 |
+----+----------+-----+-----------+----------+

The following code is an example, which would fetch the ID, Name and Salary fields of the customers available in CUSTOMERS table.

SQL> SELECT ID, NAME, SALARY FROM CUSTOMERS;

This would produce the following result −

+----+----------+----------+
| ID | NAME     | SALARY   |
+----+----------+----------+
|  1 | Ramesh   |  2000.00 |
|  2 | Khilan   |  1500.00 |
|  3 | kaushik  |  2000.00 |
|  4 | Chaitap |  6500.00 |
|  5 | Hardik   |  8500.00 |
|  6 | Komal    |  4500.00 |
|  7 | Muffy    | 10000.00 |
+----+----------+----------+

If you want to fetch all the fields of the CUSTOMERS table, then you should use the following query.

SQL> SELECT * FROM CUSTOMERS;

This would produce the result as shown below.

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

SQL - WHERE Clause

The SQL WHERE clause is used to specify a condition while fetching the data from a single table or by joining with multiple tables. If the given condition is satisfied, then only it returns a specific value from the table. You should use the WHERE clause to filter the records and fetching only the necessary records.

The WHERE clause is not only used in the SELECT statement, but it is also used in the UPDATE, DELETE statement, etc., which we would examine in the subsequent chapters.

Syntax

The basic syntax of the SELECT statement with the WHERE clause is as shown below.

SELECT column1, column2, columnN 
FROM table_name
WHERE [condition]

You can specify a condition using the comparison or logical operators pke >, <, =, LIKE, NOT, etc. The following examples would make this concept clear.

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 | Chaitap |  25 | Mumbai    |  6500.00 |
|  5 | Hardik   |  27 | Bhopal    |  8500.00 |
|  6 | Komal    |  22 | MP        |  4500.00 |
|  7 | Muffy    |  24 | Indore    | 10000.00 |
+----+----------+-----+-----------+----------+

The following code is an example which would fetch the ID, Name and Salary fields from the CUSTOMERS table, where the salary is greater than 2000 −

SQL> SELECT ID, NAME, SALARY 
FROM CUSTOMERS
WHERE SALARY > 2000;

This would produce the following result −

+----+----------+----------+
| ID | NAME     | SALARY   |
+----+----------+----------+
|  4 | Chaitap |  6500.00 |
|  5 | Hardik   |  8500.00 |
|  6 | Komal    |  4500.00 |
|  7 | Muffy    | 10000.00 |
+----+----------+----------+

The following query is an example, which would fetch the ID, Name and Salary fields from the CUSTOMERS table for a customer with the name Hardik.

SQL> SELECT ID, NAME, SALARY 
FROM CUSTOMERS
WHERE NAME =  Hardik ;

This would produce the following result −

+----+----------+----------+
| ID | NAME     | SALARY   |
+----+----------+----------+
|  5 | Hardik   |  8500.00 |
+----+----------+----------+

SQL - AND and OR Conjunctive Operators

The SQL AND & OR operators are used to combine multiple conditions to narrow data in an SQL statement. These two operators are called as the conjunctive operators.

These operators provide a means to make multiple comparisons with different operators in the same SQL statement.

The AND Operator

The AND operator allows the existence of multiple conditions in an SQL statement s WHERE clause.

Syntax

The basic syntax of the AND operator with a WHERE clause is as follows −

SELECT column1, column2, columnN 
FROM table_name
WHERE [condition1] AND [condition2]...AND [conditionN];

You can combine N number of conditions using the AND operator. For an action to be taken by the SQL statement, whether it be a transaction or a query, all conditions separated by the AND must be TRUE.

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 | Chaitap |  25 | Mumbai    |  6500.00 |
|  5 | Hardik   |  27 | Bhopal    |  8500.00 |
|  6 | Komal    |  22 | MP        |  4500.00 |
|  7 | Muffy    |  24 | Indore    | 10000.00 |
+----+----------+-----+-----------+----------+

Following is an example, which would fetch the ID, Name and Salary fields from the CUSTOMERS table, where the salary is greater than 2000 and the age is less than 25 years −

SQL> SELECT ID, NAME, SALARY 
FROM CUSTOMERS
WHERE SALARY > 2000 AND age < 25;

This would produce the following result −

+----+-------+----------+
| ID | NAME  | SALARY   |
+----+-------+----------+
|  6 | Komal |  4500.00 |
|  7 | Muffy | 10000.00 |
+----+-------+----------+

The OR Operator

The OR operator is used to combine multiple conditions in an SQL statement s WHERE clause.

Syntax

The basic syntax of the OR operator with a WHERE clause is as follows −

SELECT column1, column2, columnN 
FROM table_name
WHERE [condition1] OR [condition2]...OR [conditionN]

You can combine N number of conditions using the OR operator. For an action to be taken by the SQL statement, whether it be a transaction or query, the only any ONE of the conditions separated by the OR must be TRUE.

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 | Chaitap |  25 | Mumbai    |  6500.00 |
|  5 | Hardik   |  27 | Bhopal    |  8500.00 |
|  6 | Komal    |  22 | MP        |  4500.00 |
|  7 | Muffy    |  24 | Indore    | 10000.00 |
+----+----------+-----+-----------+----------+

The following code block hasa query, which would fetch the ID, Name and Salary fields from the CUSTOMERS table, where the salary is greater than 2000 OR the age is less than 25 years.

SQL> SELECT ID, NAME, SALARY 
FROM CUSTOMERS
WHERE SALARY > 2000 OR age < 25;

This would produce the following result −

+----+----------+----------+
| ID | NAME     | SALARY   |
+----+----------+----------+
|  3 | kaushik  |  2000.00 |
|  4 | Chaitap |  6500.00 |
|  5 | Hardik   |  8500.00 |
|  6 | Komal    |  4500.00 |
|  7 | Muffy    | 10000.00 |
+----+----------+----------+

SQL - UPDATE Query

The SQL UPDATE Query is used to modify the existing records in a table. You can use the WHERE clause with the UPDATE query to update the selected rows, otherwise all the rows would be affected.

Syntax

The basic syntax of the UPDATE query with a WHERE clause is as follows −

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

You can combine N number of conditions using the AND or the OR operators.

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 | Chaitap |  25 | Mumbai    |  6500.00 |
|  5 | Hardik   |  27 | Bhopal    |  8500.00 |
|  6 | Komal    |  22 | MP        |  4500.00 |
|  7 | Muffy    |  24 | Indore    | 10000.00 |
+----+----------+-----+-----------+----------+

The following query will update the ADDRESS for a customer whose ID number is 6 in the table.

SQL> UPDATE CUSTOMERS
SET ADDRESS =  Pune 
WHERE ID = 6;

Now, the CUSTOMERS table would have 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 | Chaitap |  25 | Mumbai    |  6500.00 |
|  5 | Hardik   |  27 | Bhopal    |  8500.00 |
|  6 | Komal    |  22 | Pune      |  4500.00 |
|  7 | Muffy    |  24 | Indore    | 10000.00 |
+----+----------+-----+-----------+----------+

If you want to modify all the ADDRESS and the SALARY column values in the CUSTOMERS table, you do not need to use the WHERE clause as the UPDATE query would be enough as shown in the following code block.

SQL> UPDATE CUSTOMERS
SET ADDRESS =  Pune , SALARY = 1000.00;

Now, CUSTOMERS table would have the following records −

+----+----------+-----+---------+---------+
| ID | NAME     | AGE | ADDRESS | SALARY  |
+----+----------+-----+---------+---------+
|  1 | Ramesh   |  32 | Pune    | 1000.00 |
|  2 | Khilan   |  25 | Pune    | 1000.00 |
|  3 | kaushik  |  23 | Pune    | 1000.00 |
|  4 | Chaitap |  25 | Pune    | 1000.00 |
|  5 | Hardik   |  27 | Pune    | 1000.00 |
|  6 | Komal    |  22 | Pune    | 1000.00 |
|  7 | Muffy    |  24 | Pune    | 1000.00 |
+----+----------+-----+---------+---------+

SQL - DELETE Query

The SQL DELETE Query is used to delete the existing records from a table.

You can use the WHERE clause with a DELETE query to delete the selected rows, otherwise all the records would be deleted.

Syntax

The basic syntax of the DELETE query with the WHERE clause is as follows −

DELETE FROM table_name
WHERE [condition];

You can combine N number of conditions using AND or OR operators.

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 | Chaitap |  25 | Mumbai    |  6500.00 |
|  5 | Hardik   |  27 | Bhopal    |  8500.00 |
|  6 | Komal    |  22 | MP        |  4500.00 |
|  7 | Muffy    |  24 | Indore    | 10000.00 |
+----+----------+-----+-----------+----------+

The following code has a query, which will DELETE a customer, whose ID is 6.

SQL> DELETE FROM CUSTOMERS
WHERE ID = 6;

Now, the CUSTOMERS table would have 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 | Chaitap |  25 | Mumbai    |  6500.00 |
|  5 | Hardik   |  27 | Bhopal    |  8500.00 |
|  7 | Muffy    |  24 | Indore    | 10000.00 |
+----+----------+-----+-----------+----------+

If you want to DELETE all the records from the CUSTOMERS table, you do not need to use the WHERE clause and the DELETE query would be as follows −

SQL> DELETE FROM CUSTOMERS;

Now, the CUSTOMERS table would not have any record.

SQL - LIKE Clause

The SQL LIKE clause is used to compare a value to similar values using wildcard operators. There are two wildcards used in conjunction with the LIKE operator.

The percent sign (%)

The underscore (_)

The percent sign represents zero, one or multiple characters. The underscore represents a single number or character. These symbols can be used in combinations.

Syntax

The basic syntax of % and _ is as follows −

SELECT FROM table_name
WHERE column LIKE  XXXX% 

or 

SELECT FROM table_name
WHERE column LIKE  %XXXX% 

or

SELECT FROM table_name
WHERE column LIKE  XXXX_ 

or

SELECT FROM table_name
WHERE column LIKE  _XXXX 

or

SELECT FROM table_name
WHERE column LIKE  _XXXX_ 

You can combine N number of conditions using AND or OR operators. Here, XXXX could be any numeric or string value.

Example

The following table has a few examples showing the WHERE part having different LIKE clause with % and _ operators −

Let us take a real example, consider the CUSTOMERS table having the records as shown below.

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

Following is an example, which would display all the records from the CUSTOMERS table, where the SALARY starts with 200.

SQL> SELECT * FROM CUSTOMERS
WHERE SALARY LIKE  200% ;

This would produce the following result −

+----+----------+-----+-----------+----------+
| ID | NAME     | AGE | ADDRESS   | SALARY   |
+----+----------+-----+-----------+----------+
|  1 | Ramesh   |  32 | Ahmedabad |  2000.00 |
|  3 | kaushik  |  23 | Kota      |  2000.00 |
+----+----------+-----+-----------+----------+

SQL - TOP, LIMIT or ROWNUM Clause

The SQL TOP clause is used to fetch a TOP N number or X percent records from a table.

Note − All the databases do not support the TOP clause. For example MySQL supports the LIMIT clause to fetch pmited number of records while Oracle uses the ROWNUM command to fetch a pmited number of records.

Syntax

The basic syntax of the TOP clause with a SELECT statement would be as follows.

SELECT TOP number|percent column_name(s)
FROM table_name
WHERE [condition]

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 | Chaitap |  25 | Mumbai    |  6500.00 |
|  5 | Hardik   |  27 | Bhopal    |  8500.00 |
|  6 | Komal    |  22 | MP        |  4500.00 |
|  7 | Muffy    |  24 | Indore    | 10000.00 |
+----+----------+-----+-----------+----------+

The following query is an example on the SQL server, which would fetch the top 3 records from the CUSTOMERS table.

SQL> SELECT TOP 3 * FROM CUSTOMERS;

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 |
+----+---------+-----+-----------+---------+

If you are using MySQL server, then here is an equivalent example −

SQL> SELECT * FROM CUSTOMERS
LIMIT 3;

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 |
+----+---------+-----+-----------+---------+

If you are using an Oracle server, then the following code block has an equivalent example.

SQL> SELECT * FROM CUSTOMERS
WHERE ROWNUM <= 3;

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 |
+----+---------+-----+-----------+---------+

SQL - ORDER BY Clause

The SQL ORDER BY clause is used to sort the data in ascending or descending order, based on one or more columns. Some databases sort the query results in an ascending order by default.

Syntax

The basic syntax of the ORDER BY clause is as follows −

SELECT column-pst 
FROM table_name 
[WHERE condition] 
[ORDER BY column1, column2, .. columnN] [ASC | DESC];

You can use more than one column in the ORDER BY clause. Make sure whatever column you are using to sort that column should be in the column-pst.

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 | Chaitap |  25 | Mumbai    |  6500.00 |
|  5 | Hardik   |  27 | Bhopal    |  8500.00 |
|  6 | Komal    |  22 | MP        |  4500.00 |
|  7 | Muffy    |  24 | Indore    | 10000.00 |
+----+----------+-----+-----------+----------+

The following code block has an example, which would sort the result in an ascending order by the NAME and the SALARY −

SQL> SELECT * FROM CUSTOMERS
   ORDER BY NAME, SALARY;

This would produce the following result −

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

The following code block has an example, which would sort the result in the descending order by NAME.

SQL> SELECT * FROM CUSTOMERS
   ORDER BY NAME DESC;

This would produce the following result −

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

SQL - Group By

The SQL GROUP BY clause is used in collaboration with the SELECT statement to arrange identical data into groups. This GROUP BY clause follows the WHERE clause in a SELECT statement and precedes the ORDER BY clause.

Syntax

The basic syntax of a GROUP BY clause is shown in the following code block. The GROUP BY clause must follow the conditions in the WHERE clause and must precede the ORDER BY clause if one is used.

SELECT column1, column2
FROM table_name
WHERE [ conditions ]
GROUP BY column1, column2
ORDER BY column1, column2

Example

Consider the CUSTOMERS table is 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 | Chaitap |  25 | Mumbai    |  6500.00 |
|  5 | Hardik   |  27 | Bhopal    |  8500.00 |
|  6 | Komal    |  22 | MP        |  4500.00 |
|  7 | Muffy    |  24 | Indore    | 10000.00 |
+----+----------+-----+-----------+----------+

If you want to know the total amount of the salary on each customer, then the GROUP BY query would be as follows.

SQL> SELECT NAME, SUM(SALARY) FROM CUSTOMERS
   GROUP BY NAME;

This would produce the following result −

+----------+-------------+
| NAME     | SUM(SALARY) |
+----------+-------------+
| Chaitap |     6500.00 |
| Hardik   |     8500.00 |
| kaushik  |     2000.00 |
| Khilan   |     1500.00 |
| Komal    |     4500.00 |
| Muffy    |    10000.00 |
| Ramesh   |     2000.00 |
+----------+-------------+

Now, let us look at a table where the CUSTOMERS table has the following records with duppcate names −

+----+----------+-----+-----------+----------+
| 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 |
+----+----------+-----+-----------+----------+

Now again, if you want to know the total amount of salary on each customer, then the GROUP BY query would be as follows −

SQL> SELECT NAME, SUM(SALARY) FROM CUSTOMERS
   GROUP BY NAME;

This would produce the following result −

+---------+-------------+
| NAME    | SUM(SALARY) |
+---------+-------------+
| Hardik  |     8500.00 |
| kaushik |     8500.00 |
| Komal   |     4500.00 |
| Muffy   |    10000.00 |
| Ramesh  |     3500.00 |
+---------+-------------+

SQL - Distinct Keyword

The SQL DISTINCT keyword is used in conjunction with the SELECT statement to epminate all the duppcate records and fetching only unique records.

There may be a situation when you have multiple duppcate records in a table. While fetching such records, it makes more sense to fetch only those unique records instead of fetching duppcate records.

Syntax

The basic syntax of DISTINCT keyword to epminate the duppcate records is as follows −

SELECT DISTINCT column1, column2,.....columnN 
FROM table_name
WHERE [condition]

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 | Chaitap |  25 | Mumbai    |  6500.00 |
|  5 | Hardik   |  27 | Bhopal    |  8500.00 |
|  6 | Komal    |  22 | MP        |  4500.00 |
|  7 | Muffy    |  24 | Indore    | 10000.00 |
+----+----------+-----+-----------+----------+

First, let us see how the following SELECT query returns the duppcate salary records.

SQL> SELECT SALARY FROM CUSTOMERS
   ORDER BY SALARY;

This would produce the following result, where the salary (2000) is coming twice which is a duppcate record from the original table.

+----------+
| SALARY   |
+----------+
|  1500.00 |
|  2000.00 |
|  2000.00 |
|  4500.00 |
|  6500.00 |
|  8500.00 |
| 10000.00 |
+----------+

Now, let us use the DISTINCT keyword with the above SELECT query and then see the result.

SQL> SELECT DISTINCT SALARY FROM CUSTOMERS
   ORDER BY SALARY;

This would produce the following result where we do not have any duppcate entry.

+----------+
| SALARY   |
+----------+
|  1500.00 |
|  2000.00 |
|  4500.00 |
|  6500.00 |
|  8500.00 |
| 10000.00 |
+----------+

SQL - SORTING Results

The SQL ORDER BY clause is used to sort the data in ascending or descending order, based on one or more columns. Some databases sort the query results in an ascending order by default.

Syntax

The basic syntax of the ORDER BY clause which would be used to sort the result in an ascending or descending order is as follows −

SELECT column-pst 
FROM table_name 
[WHERE condition] 
[ORDER BY column1, column2, .. columnN] [ASC | DESC];

You can use more than one column in the ORDER BY clause. Make sure that whatever column you are using to sort, that column should be in the column-pst.

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 | Chaitap |  25 | Mumbai    |  6500.00 |
|  5 | Hardik   |  27 | Bhopal    |  8500.00 |
|  6 | Komal    |  22 | MP        |  4500.00 |
|  7 | Muffy    |  24 | Indore    | 10000.00 |
+----+----------+-----+-----------+----------+

Following is an example, which would sort the result in an ascending order by NAME and SALARY.

SQL> SELECT * FROM CUSTOMERS
   ORDER BY NAME, SALARY;

This would produce the following result −

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

The following code block has an example, which would sort the result in a descending order by NAME.

SQL> SELECT * FROM CUSTOMERS
   ORDER BY NAME DESC;

This would produce the following result −

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

To fetch the rows with their own preferred order, the SELECT query used would be as follows −

SQL> SELECT * FROM CUSTOMERS
   ORDER BY (CASE ADDRESS
   WHEN  DELHI  	 THEN 1
   WHEN  BHOPAL  	 THEN 2
   WHEN  KOTA  	 THEN 3
   WHEN  AHMEDABAD  THEN 4
   WHEN  MP  	THEN 5
   ELSE 100 END) ASC, ADDRESS DESC;

This would produce the following result −

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

This will sort the customers by ADDRESS in your ownoOrder of preference first and in a natural order for the remaining addresses. Also, the remaining Addresses will be sorted in the reverse alphabetical order.

SQL - Constraints

Constraints are the rules enforced on the data columns of a table. These are used to pmit the type of data that can go into a table. This ensures the accuracy and repabipty of the data in the database.

Constraints could be either on a column level or a table level. The column level constraints are appped only to one column, whereas the table level constraints are appped to the whole table.

Following are some of the most commonly used constraints available in SQL. These constraints have already been discussed in SQL - RDBMS Concepts chapter, but it’s 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 identifies each row/record in a database table.

FOREIGN Key − Uniquely identifies a row/record in any of the given database table.

CHECK Constraint − The CHECK constraint ensures that all the values in a column satisfies certain conditions.

INDEX − Used 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 the 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 the 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 which are mentioned above.

SQL - Using Joins

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 −

Table 1 − CUSTOMERS Table

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

Table 2 − ORDERS Table

+-----+---------------------+-------------+--------+
|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 shown below.

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 | Chaitap |  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 to symbol.

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.

Let us now discuss each of these joins in detail.

SQL - UNIONS CLAUSE

The SQL UNION clause/operator is used to combine the results of two or more SELECT statements without returning any duppcate rows.

To use this UNION clause, each SELECT statement 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 need not have to be in the same length.

Syntax

The basic syntax of a UNION clause is as follows −

SELECT column1 [, column2 ]
FROM table1 [, table2 ]
[WHERE condition]

UNION

SELECT column1 [, column2 ]
FROM table1 [, table2 ]
[WHERE condition]

Here, the given condition could be any given expression based on your requirement.

Example

Consider the following two tables.

Table 1 − 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 | Chaitap |  25 | Mumbai    |  6500.00 |
|  5 | Hardik   |  27 | Bhopal    |  8500.00 |
|  6 | Komal    |  22 | MP        |  4500.00 |
|  7 | Muffy    |  24 | Indore    | 10000.00 |
+----+----------+-----+-----------+----------+

Table 2 − ORDERS Table is 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 | Chaitap |   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 duppcate rows.

The same rules that apply to the UNION clause will apply to the UNION ALL operator.

Syntax

The basic syntax of the UNION ALL is as follows.

SELECT column1 [, column2 ]
FROM table1 [, table2 ]
[WHERE condition]

UNION ALL

SELECT column1 [, column2 ]
FROM table1 [, table2 ]
[WHERE condition]

Here, the given condition could be any given expression based on your requirement.

Example

Consider the following two tables,

Table 1 − 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 | Chaitap |  25 | Mumbai    |  6500.00 |
|  5 | Hardik   |  27 | Bhopal    |  8500.00 |
|  6 | Komal    |  22 | MP        |  4500.00 |
|  7 | Muffy    |  24 | Indore    | 10000.00 |
+----+----------+-----+-----------+----------+

Table 2 − ORDERS table is 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 | Chaitap |   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 | Chaitap |   2060 | 2008-05-20 00:00:00 |
+------+----------+--------+---------------------+

There are two other clauses (i.e., operators), which are pke the UNION clause.

SQL INTERSECT Clause − This 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 − This combines two SELECT statements and returns rows from the first SELECT statement that are not returned by the second SELECT statement.

SQL - NULL Values

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 exppcit 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 the one that has been left blank during the 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 results. You must use the IS NULL or IS NOT NULL operators to check for a NULL value.

Consider the following CUSTOMERS table having the records as shown below.

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

Now, following is the usage of the IS NOT NULLoperator.

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 | Chaitap |  25 | Mumbai    |  6500.00 |
|  5 | Hardik   |  27 | Bhopal    |  8500.00 |
+----+----------+-----+-----------+----------+

Now, following is the usage of the 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    |          |
+----+----------+-----+-----------+----------+

SQL - Apas Syntax

You can rename a table or a column temporarily by giving another name known as Apas. The use of table apases is to rename a table in a specific SQL statement. The renaming is a temporary change and the actual table name does not change in the database. The column apases are used to rename a table s columns for the purpose of a particular SQL query.

Syntax

The basic syntax of a table apas is as follows.

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

The basic syntax of a column apas is as follows.

SELECT column_name AS apas_name
FROM table_name
WHERE [condition];

Example

Consider the following two tables.

Table 1 − 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 | Chaitap |  25 | Mumbai    |  6500.00 |
|  5 | Hardik   |  27 | Bhopal    |  8500.00 |
|  6 | Komal    |  22 | MP        |  4500.00 |
|  7 | Muffy    |  24 | Indore    | 10000.00 |
+----+----------+-----+-----------+----------+

Table 2 − ORDERS Table is 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, the following code block shows the usage of a table apas.

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 | Chaitap |  25 |   2060 |
+----+----------+-----+--------+

Following is the usage of a column apas.

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 | Chaitap      |
|           5 | Hardik        |
|           6 | Komal         |
|           7 | Muffy         |
+-------------+---------------+

SQL - Indexes

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 discusses a certain topic, you first refer to the index, which psts all the topics alphabetically and are then referred to one or more specific page numbers.

An index helps to speed up SELECT queries and WHERE clauses, but it slows down data input, with the UPDATE and the 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 an ascending or descending order.

Indexes can also be unique, pke the UNIQUE constraint, in that the index prevents duppcate entries in the column or combination of columns on which there is an index.

The CREATE INDEX Command

The basic syntax of a CREATE INDEX is as follows.

CREATE INDEX index_name ON table_name;

Single-Column Indexes

A single-column index 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 duppcate 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. Its 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.

Imppcit Indexes

Imppcit 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 the performance may either slow down or improve.

The basic syntax is as follows −

DROP INDEX index_name;

You can check the INDEX Constraint chapter to see some 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 guidepnes indicate when the use of an index should be reconsidered.

Indexes should not be used on small tables.

Tables that have frequent, large batch updates 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.

SQL - ALTER TABLE Command

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

Syntax

The basic syntax of an ALTER TABLE command to add a New Column in an existing table is as follows.

ALTER TABLE table_name ADD column_name datatype;

The basic syntax of an ALTER TABLE command to DROP COLUMN in an existing table is as follows.

ALTER TABLE table_name DROP COLUMN column_name;

The basic syntax of an ALTER TABLE command 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 an ALTER TABLE command 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 an ALTER TABLE command to ADD CHECK CONSTRAINT to a table is as follows.

ALTER TABLE table_name 
ADD CONSTRAINT MyUniqueConstraint CHECK (CONDITION);

The basic syntax of an ALTER TABLE command 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 an ALTER TABLE command 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 an ALTER TABLE command 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 | Chaitap |  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 to an existing table −

ALTER TABLE CUSTOMERS ADD SEX char(1);

Now, the CUSTOMERS table is changed and following would be output from the 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 the existing table.

ALTER TABLE CUSTOMERS DROP SEX;

Now, the CUSTOMERS table is changed and following would be the output from the 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 |
+----+---------+-----+-----------+----------+

SQL - TRUNCATE TABLE Command

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 a TRUNCATE TABLE command is as follows.

TRUNCATE TABLE  table_name;

Example

Consider a 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 | Chaitap |  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 of a Truncate command.

SQL > TRUNCATE TABLE CUSTOMERS;

Now, the CUSTOMERS table is truncated and the output from SELECT statement will be as shown in the code block below −

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

SQL - Using Views

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 a type 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 in such a way 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 a similar way as you use them in a 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 | Chaitap |  25 | Mumbai    |  6500.00 |
|  5 | Hardik   |  27 | Bhopal    |  8500.00 |
|  6 | Komal    |  22 | MP        |  4500.00 |
|  7 | Muffy    |  24 | Indore    | 10000.00 |
+----+----------+-----+-----------+----------+

Following is an example to create a view from the CUSTOMERS table. This view would be used to have customer name and age from the CUSTOMERS table.

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

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

SQL > SELECT * FROM CUSTOMERS_VIEW;

This would produce the following result.

+----------+-----+
| name     | age |
+----------+-----+
| Ramesh   |  32 |
| Khilan   |  25 |
| kaushik  |  23 |
| Chaitap |  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 code block has 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 which are given below −

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 that view. The following code block has 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 the same would reflect in the view itself. Now, try to query the base table and the 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 | Chaitap |  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 cannot insert rows in the CUSTOMERS_VIEW because we have not included all the NOT NULL columns in this view, otherwise you can insert rows in a view in a 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 the same would reflect in the view itself. Now, try to query the base table and the 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 | Chaitap |  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 and is given below −

DROP VIEW view_name;

Following is an example to drop the CUSTOMERS_VIEW from the CUSTOMERS table.

DROP VIEW CUSTOMERS_VIEW;

SQL - Having Clause

The HAVING Clause enables you to specify conditions that filter which group results appear in the 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 code block shows 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 code block has 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 | Chaitap |  25 | Mumbai    |  6500.00 |
|  5 | Hardik   |  27 | Bhopal    |  8500.00 |
|  6 | Komal    |  22 | MP        |  4500.00 |
|  7 | Muffy    |  24 | Indore    | 10000.00 |
+----+----------+-----+-----------+----------+

Following is an example, which would display a record for a similar age count that 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 |
+----+--------+-----+---------+---------+

SQL - Transactions

A transaction is a unit of work that is performed against a database. Transactions are units or sequences of work accomppshed 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 a transaction on that table. It is important to control these transactions to ensure the 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 all the 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.

Durabipty − ensures that the result or effect of a committed transaction persists in case of a system failure.

Transaction Control

The following commands are used to control transactions.

COMMIT − to save the changes.

ROLLBACK − to roll back the changes.

SAVEPOINT − creates points within the groups of transactions in which to ROLLBACK.

SET TRANSACTION − Places a name on a transaction.

Transactional Control Commands

Transactional control commands are only used with the DML Commands such as - INSERT, UPDATE and DELETE only. They cannot be used while creating tables or dropping them because these operations are automatically committed 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 is the transactional command used to save changes invoked by a transaction to the database. The COMMIT command saves all the transactions to the database since the last COMMIT or ROLLBACK command.

The syntax for the 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 | Chaitap |  25 | Mumbai    |  6500.00 |
|  5 | Hardik   |  27 | Bhopal    |  8500.00 |
|  6 | Komal    |  22 | MP        |  4500.00 |
|  7 | Muffy    |  24 | Indore    | 10000.00 |
+----+----------+-----+-----------+----------+

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

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

Thus, two rows from the table would be deleted and the 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. This command can only be used to undo transactions since the last COMMIT or ROLLBACK command was issued.

The syntax for a 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 | Chaitap |  25 | Mumbai    |  6500.00 |
|  5 | Hardik   |  27 | Bhopal    |  8500.00 |
|  6 | Komal    |  22 | MP        |  4500.00 |
|  7 | Muffy    |  24 | Indore    | 10000.00 |
+----+----------+-----+-----------+----------+

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

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

Thus, the delete operation would not impact the table and the 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 | Chaitap |  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 rolpng back the entire transaction.

The syntax for a SAVEPOINT command is as shown below.

SAVEPOINT SAVEPOINT_NAME;

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

The syntax for rolpng back to a SAVEPOINT is as shown below.

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 | Chaitap |  25 | Mumbai    |  6500.00 |
|  5 | Hardik   |  27 | Bhopal    |  8500.00 |
|  6 | Komal    |  22 | MP        |  4500.00 |
|  7 | Muffy    |  24 | Indore    | 10000.00 |
+----+----------+-----+-----------+----------+

The following code block contains 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, let us assume that 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 | Chaitap |  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 a RELEASE SAVEPOINT command 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 last 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 a SET TRANSACTION command is as follows.

SET TRANSACTION [ READ WRITE | READ ONLY ];

SQL - Wildcard Operators

We have already discussed about the SQL LIKE operator, which is used to compare a value to similar values using the wildcard operators.

SQL supports two wildcard operators in conjunction with the LIKE operator which are explained in detail in the following table.

The percent sign represents zero, one or multiple characters. The underscore represents a single number or a character. These symbols can be used in combinations.

Syntax

The basic syntax of a % and a _ operator is as follows.

SELECT * FROM table_name
WHERE column LIKE  XXXX% 

or 

SELECT * FROM table_name
WHERE column LIKE  %XXXX% 

or

SELECT * FROM table_name
WHERE column LIKE  XXXX_ 

or

SELECT * FROM table_name
WHERE column LIKE  _XXXX 

or

SELECT * FROM table_name
WHERE column LIKE  _XXXX_ 

You can combine N number of conditions using the AND or the OR operators. Here, XXXX could be any numeric or string value.

Example

The following table has a number of examples showing the WHERE part having different LIKE clauses with % and _ operators.

Let us take a real 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 | Chaitap |  25 | Mumbai    |  6500.00 |
|  5 | Hardik   |  27 | Bhopal    |  8500.00 |
|  6 | Komal    |  22 | MP        |  4500.00 |
|  7 | Muffy    |  24 | Indore    | 10000.00 |
+----+----------+-----+-----------+----------+

The following code block is an example, which would display all the records from the CUSTOMERS table where the SALARY starts with 200.

SQL> SELECT * FROM CUSTOMERS
WHERE SALARY LIKE  200% ;

This would produce the following result.

+----+----------+-----+-----------+----------+
| ID | NAME     | AGE | ADDRESS   | SALARY   |
+----+----------+-----+-----------+----------+
|  1 | Ramesh   |  32 | Ahmedabad |  2000.00 |
|  3 | kaushik  |  23 | Kota      |  2000.00 |
+----+----------+-----+-----------+----------+

SQL - Date Functions

The following table has a pst of all the important Date and Time related functions available through SQL. There are various other functions supported by your RDBMS. The given pst is based on MySQL RDBMS.

mysql> SELECT DATE_ADD( 1998-01-02 , INTERVAL 31 DAY);
+---------------------------------------------------------+
| DATE_ADD( 1998-01-02 , INTERVAL 31 DAY)                 |
+---------------------------------------------------------+
| 1998-02-02                                              |
+---------------------------------------------------------+
1 row in set (0.00 sec)

mysql> SELECT ADDDATE( 1998-01-02 , INTERVAL 31 DAY);
+---------------------------------------------------------+
| ADDDATE( 1998-01-02 , INTERVAL 31 DAY)                  |
+---------------------------------------------------------+
| 1998-02-02                                              |
+---------------------------------------------------------+
1 row in set (0.00 sec)

mysql> SELECT ADDDATE( 1998-01-02 , 31);
+---------------------------------------------------------+
| DATE_ADD( 1998-01-02 , INTERVAL 31 DAY)                 |
+---------------------------------------------------------+
| 1998-02-02                                              |
+---------------------------------------------------------+
1 row in set (0.00 sec)

mysql> SELECT ADDTIME( 1997-12-31 23:59:59.999999 , 1 1:1:1.000002 );
+---------------------------------------------------------+
| DATE_ADD( 1997-12-31 23:59:59.999999 , 1 1:1:1.000002 ) |
+---------------------------------------------------------+
| 1998-01-02 01:01:01.000001                              |
+---------------------------------------------------------+
1 row in set (0.00 sec)

mysql> SELECT CONVERT_TZ( 2004-01-01 12:00:00 , GMT , MET );
+---------------------------------------------------------+
| CONVERT_TZ( 2004-01-01 12:00:00 , GMT , MET )           |
+---------------------------------------------------------+
| 2004-01-01 13:00:00                                     |
+---------------------------------------------------------+
1 row in set (0.00 sec)

mysql> SELECT CONVERT_TZ( 2004-01-01 12:00:00 , +00:00 , +10:00 );
+---------------------------------------------------------+
| CONVERT_TZ( 2004-01-01 12:00:00 , +00:00 , +10:00 )     |
+---------------------------------------------------------+
| 2004-01-01 22:00:00                                     |
+---------------------------------------------------------+
1 row in set (0.00 sec)

mysql> SELECT CURDATE();
+---------------------------------------------------------+
| CURDATE()                                               |
+---------------------------------------------------------+
| 1997-12-15                                              |
+---------------------------------------------------------+
1 row in set (0.00 sec)

mysql> SELECT CURDATE() + 0;
+---------------------------------------------------------+
| CURDATE() + 0                                           |
+---------------------------------------------------------+
| 19971215                                                |
+---------------------------------------------------------+
1 row in set (0.00 sec)

mysql> SELECT CURTIME();
+---------------------------------------------------------+
| CURTIME()                                               |
+---------------------------------------------------------+
| 23:50:26                                                |
+---------------------------------------------------------+
1 row in set (0.00 sec)

mysql> SELECT CURTIME() + 0;
+---------------------------------------------------------+
| CURTIME() + 0                                           |
+---------------------------------------------------------+
| 235026                                                  |
+---------------------------------------------------------+
1 row in set (0.00 sec)

mysql> SELECT DATE( 2003-12-31 01:02:03 );
+---------------------------------------------------------+
| DATE( 2003-12-31 01:02:03 )                             |
+---------------------------------------------------------+
|  2003-12-31                                             |
+---------------------------------------------------------+
1 row in set (0.00 sec)

mysql> SELECT DATEDIFF( 1997-12-31 23:59:59 , 1997-12-30 );
+---------------------------------------------------------+
| DATEDIFF( 1997-12-31 23:59:59 , 1997-12-30 )            |
+---------------------------------------------------------+
| 1                                                       |
+---------------------------------------------------------+
1 row in set (0.00 sec)

mysql> SELECT DATE_ADD( 1997-12-31 23:59:59 , 
   -> INTERVAL  1:1  MINUTE_SECOND);
+---------------------------------------------------------+
| DATE_ADD( 1997-12-31 23:59:59 , INTERVAL...             |
+---------------------------------------------------------+
| 1998-01-01 00:01:00                                     |
+---------------------------------------------------------+
1 row in set (0.00 sec)

mysql> SELECT DATE_ADD( 1999-01-01 , INTERVAL 1 HOUR);
+---------------------------------------------------------+
| DATE_ADD( 1999-01-01 , INTERVAL 1 HOUR)                 |
+---------------------------------------------------------+
| 1999-01-01 01:00:00                                     |
+---------------------------------------------------------+
1 row in set (0.00 sec)

mysql> SELECT DATE_FORMAT( 1997-10-04 22:23:00 ,  %W %M %Y );
+---------------------------------------------------------+
| DATE_FORMAT( 1997-10-04 22:23:00 ,  %W %M %Y )          |
+---------------------------------------------------------+
| Saturday October 1997                                   |
+---------------------------------------------------------+
1 row in set (0.00 sec)

mysql> SELECT DATE_FORMAT( 1997-10-04 22:23:00 
   ->  %H %k %I %r %T %S %w );
+---------------------------------------------------------+
| DATE_FORMAT( 1997-10-04 22:23:00.......                 |
+---------------------------------------------------------+
|  22 22 10 10:23:00 PM 22:23:00 00 6                     |
+---------------------------------------------------------+
1 row in set (0.00 sec)

mysql> SELECT DAYNAME( 1998-02-05 );
+---------------------------------------------------------+
| DAYNAME( 1998-02-05 )                                   |
+---------------------------------------------------------+
| Thursday                                                |
+---------------------------------------------------------+
1 row in set (0.00 sec)

mysql> SELECT DAYOFMONTH( 1998-02-03 );
+---------------------------------------------------------+
| DAYOFMONTH( 1998-02-03 )                                |
+---------------------------------------------------------+
| 3                                                       |
+---------------------------------------------------------+
1 row in set (0.00 sec)

mysql> SELECT DAYOFWEEK( 1998-02-03 );
+---------------------------------------------------------+
|DAYOFWEEK( 1998-02-03 )                                  |
+---------------------------------------------------------+
| 3                                                       |
+---------------------------------------------------------+
1 row in set (0.00 sec)

mysql> SELECT DAYOFYEAR( 1998-02-03 );
+---------------------------------------------------------+
| DAYOFYEAR( 1998-02-03 )                                 |
+---------------------------------------------------------+
| 34                                                      |
+---------------------------------------------------------+
1 row in set (0.00 sec)

mysql> SELECT EXTRACT(YEAR FROM  1999-07-02 );
+---------------------------------------------------------+
| EXTRACT(YEAR FROM  1999-07-02 )                         |
+---------------------------------------------------------+
| 1999                                                    |
+---------------------------------------------------------+
1 row in set (0.00 sec)

mysql> SELECT EXTRACT(YEAR_MONTH FROM  1999-07-02 01:02:03 );
+---------------------------------------------------------+
| EXTRACT(YEAR_MONTH FROM  1999-07-02 01:02:03 )          |
+---------------------------------------------------------+
| 199907                                                  |
+---------------------------------------------------------+
1 row in set (0.00 sec)

mysql> SELECT FROM_DAYS(729669);
+---------------------------------------------------------+
| FROM_DAYS(729669)                                       |
+---------------------------------------------------------+
| 1997-10-07                                              |
+---------------------------------------------------------+
1 row in set (0.00 sec)

mysql> SELECT FROM_UNIXTIME(875996580);
+---------------------------------------------------------+
| FROM_UNIXTIME(875996580)                                |
+---------------------------------------------------------+
| 1997-10-04 22:23:00                                     |
+---------------------------------------------------------+
1 row in set (0.00 sec)

mysql> SELECT HOUR( 10:05:03 );
+---------------------------------------------------------+
| HOUR( 10:05:03 )                                        |
+---------------------------------------------------------+
| 10                                                      |
+---------------------------------------------------------+
1 row in set (0.00 sec)

mysql> SELECT LAST_DAY( 2003-02-05 );
+---------------------------------------------------------+
| LAST_DAY( 2003-02-05 )                                  |
+---------------------------------------------------------+
| 2003-02-28                                              |
+---------------------------------------------------------+
1 row in set (0.00 sec)

mysql> SELECT MAKEDATE(2001,31), MAKEDATE(2001,32);
+---------------------------------------------------------+
| MAKEDATE(2001,31), MAKEDATE(2001,32)                    |
+---------------------------------------------------------+
|  2001-01-31 ,  2001-02-01                               |
+---------------------------------------------------------+
1 row in set (0.00 sec)

mysql> SELECT MAKETIME(12,15,30);
+---------------------------------------------------------+
| MAKETIME(12,15,30)                                      |
+---------------------------------------------------------+
|  12:15:30                                               |
+---------------------------------------------------------+
1 row in set (0.00 sec)

mysql> SELECT MICROSECOND( 12:00:00.123456 );
+---------------------------------------------------------+
| MICROSECOND( 12:00:00.123456 )                          |
+---------------------------------------------------------+
| 123456                                                  |
+---------------------------------------------------------+
1 row in set (0.00 sec)

mysql> SELECT MINUTE( 98-02-03 10:05:03 );
+---------------------------------------------------------+
| MINUTE( 98-02-03 10:05:03 )                             |
+---------------------------------------------------------+
| 5                                                       |
+---------------------------------------------------------+
1 row in set (0.00 sec)

mysql> SELECT MONTH( 1998-02-03 )
+---------------------------------------------------------+
| MONTH( 1998-02-03 )                                     |
+---------------------------------------------------------+
| 2                                                       |
+---------------------------------------------------------+
1 row in set (0.00 sec)

mysql> SELECT MONTHNAME( 1998-02-05 );
+---------------------------------------------------------+
| MONTHNAME( 1998-02-05 )                                 |
+---------------------------------------------------------+
| February                                                |
+---------------------------------------------------------+
1 row in set (0.00 sec)

mysql> SELECT NOW();
+---------------------------------------------------------+
| NOW()                                                   |
+---------------------------------------------------------+
| 1997-12-15 23:50:26                                     |
+---------------------------------------------------------+
1 row in set (0.00 sec)

mysql> SELECT PERIOD_ADD(9801,2);
+---------------------------------------------------------+
| PERIOD_ADD(9801,2)                                      |
+---------------------------------------------------------+
| 199803                                                  |
+---------------------------------------------------------+
1 row in set (0.00 sec)

mysql> SELECT PERIOD_DIFF(9802,199703);
+---------------------------------------------------------+
| PERIOD_DIFF(9802,199703)                                |
+---------------------------------------------------------+
| 11                                                      |
+---------------------------------------------------------+
1 row in set (0.00 sec)

mysql> SELECT QUARTER( 98-04-01 );
+---------------------------------------------------------+
| QUARTER( 98-04-01 )                                     |
+---------------------------------------------------------+
| 2                                                       |
+---------------------------------------------------------+
1 row in set (0.00 sec)

mysql> SELECT SECOND( 10:05:03 );
+---------------------------------------------------------+
| SECOND( 10:05:03 )                                      |
+---------------------------------------------------------+
| 3                                                       |
+---------------------------------------------------------+
1 row in set (0.00 sec)

mysql> SELECT SEC_TO_TIME(2378);
+---------------------------------------------------------+
| SEC_TO_TIME(2378)                                       |
+---------------------------------------------------------+
| 00:39:38                                                |
+---------------------------------------------------------+
1 row in set (0.00 sec)

mysql> SELECT STR_TO_DATE( 04/31/2004 ,  %m/%d/%Y );
+---------------------------------------------------------+
| STR_TO_DATE( 04/31/2004 ,  %m/%d/%Y )                   |
+---------------------------------------------------------+
| 2004-04-31                                              |
+---------------------------------------------------------+
1 row in set (0.00 sec)

mysql> SELECT DATE_SUB( 1998-01-02 , INTERVAL 31 DAY);
+---------------------------------------------------------+
| DATE_SUB( 1998-01-02 , INTERVAL 31 DAY)                 |
+---------------------------------------------------------+
| 1997-12-02                                              |
+---------------------------------------------------------+
1 row in set (0.00 sec)

mysql> SELECT SUBDATE( 1998-01-02 , INTERVAL 31 DAY);
+---------------------------------------------------------+
| SUBDATE( 1998-01-02 , INTERVAL 31 DAY)                  |
+---------------------------------------------------------+
| 1997-12-02                                              |
+---------------------------------------------------------+
1 row in set (0.00 sec)

mysql> SELECT SUBTIME( 1997-12-31 23:59:59.999999 ,
   ->  1 1:1:1.000002 );
+---------------------------------------------------------+
| SUBTIME( 1997-12-31 23:59:59.999999 ...                 |
+---------------------------------------------------------+
| 1997-12-30 22:58:58.999997                              |
+---------------------------------------------------------+
1 row in set (0.00 sec)

mysql> SELECT SYSDATE();
+---------------------------------------------------------+
| SYSDATE()                                               |
+---------------------------------------------------------+
| 2006-04-12 13:47:44                                     |
+---------------------------------------------------------+
1 row in set (0.00 sec)

mysql> SELECT TIME( 2003-12-31 01:02:03 );
+---------------------------------------------------------+
| TIME( 2003-12-31 01:02:03 )                             |
+---------------------------------------------------------+
| 01:02:03                                                |
+---------------------------------------------------------+
1 row in set (0.00 sec)

mysql> SELECT TIMEDIFF( 1997-12-31 23:59:59.000001 ,
   ->  1997-12-30 01:01:01.000002 );
+---------------------------------------------------------+
| TIMEDIFF( 1997-12-31 23:59:59.000001 .....              |
+---------------------------------------------------------+
|  46:58:57.999999                                        |
+---------------------------------------------------------+
1 row in set (0.00 sec)

mysql> SELECT TIMESTAMP( 2003-12-31 );
+---------------------------------------------------------+
| TIMESTAMP( 2003-12-31 )                                 |
+---------------------------------------------------------+
| 2003-12-31 00:00:00                                     |
+---------------------------------------------------------+
1 row in set (0.00 sec)

mysql> SELECT TIMESTAMPADD(MINUTE,1, 2003-01-02 );
+---------------------------------------------------------+
| TIMESTAMPADD(MINUTE,1, 2003-01-02 )                     |
+---------------------------------------------------------+
| 2003-01-02 00:01:00                                     |
+---------------------------------------------------------+
1 row in set (0.00 sec)

mysql> SELECT TIMESTAMPDIFF(MONTH, 2003-02-01 , 2003-05-01 );
+---------------------------------------------------------+
| TIMESTAMPDIFF(MONTH, 2003-02-01 , 2003-05-01 )          |
+---------------------------------------------------------+
| 3                                                       |
+---------------------------------------------------------+
1 row in set (0.00 sec)

mysql> SELECT TIME_FORMAT( 100:00:00 ,  %H %k %h %I %l );
+---------------------------------------------------------+
| TIME_FORMAT( 100:00:00 ,  %H %k %h %I %l )              |
+---------------------------------------------------------+
| 100 100 04 04 4                                         |
+---------------------------------------------------------+
1 row in set (0.00 sec)

mysql> SELECT TIME_TO_SEC( 22:23:00 );
+---------------------------------------------------------+
| TIME_TO_SEC( 22:23:00 )                                 |
+---------------------------------------------------------+
| 80580                                                   |
+---------------------------------------------------------+
1 row in set (0.00 sec)

mysql> SELECT TO_DAYS(950501);
+---------------------------------------------------------+
| TO_DAYS(950501)                                         |
+---------------------------------------------------------+
| 728779                                                  |
+---------------------------------------------------------+
1 row in set (0.00 sec)

mysql> SELECT UNIX_TIMESTAMP();
+---------------------------------------------------------+
| UNIX_TIMESTAMP()                                        |
+---------------------------------------------------------+
| 882226357                                               |
+---------------------------------------------------------+
1 row in set (0.00 sec)

mysql> SELECT UNIX_TIMESTAMP( 1997-10-04 22:23:00 );
+---------------------------------------------------------+
| UNIX_TIMESTAMP( 1997-10-04 22:23:00 )                   |
+---------------------------------------------------------+
| 875996580                                               |
+---------------------------------------------------------+
1 row in set (0.00 sec)

mysql> SELECT UTC_DATE(), UTC_DATE() + 0;
+---------------------------------------------------------+
| UTC_DATE(), UTC_DATE() + 0                              |
+---------------------------------------------------------+
| 2003-08-14, 20030814                                    |
+---------------------------------------------------------+
1 row in set (0.00 sec)

mysql> SELECT UTC_TIME(), UTC_TIME() + 0;
+---------------------------------------------------------+
| UTC_TIME(), UTC_TIME() + 0                              |
+---------------------------------------------------------+
| 18:07:53, 180753                                        |
+---------------------------------------------------------+
1 row in set (0.00 sec)

mysql> SELECT UTC_TIMESTAMP(), UTC_TIMESTAMP() + 0;
+---------------------------------------------------------+
| UTC_TIMESTAMP(), UTC_TIMESTAMP() + 0                    |
+---------------------------------------------------------+
| 2003-08-14 18:08:04, 20030814180804                     |
+---------------------------------------------------------+
1 row in set (0.00 sec)

mysql> SELECT WEEK( 1998-02-20 );
+---------------------------------------------------------+
| WEEK( 1998-02-20 )                                      |
+---------------------------------------------------------+
| 7                                                       |
+---------------------------------------------------------+
1 row in set (0.00 sec)

mysql> SELECT WEEKDAY( 1998-02-03 22:23:00 );
+---------------------------------------------------------+
| WEEKDAY( 1998-02-03 22:23:00 )                          |
+---------------------------------------------------------+
| 1                                                       |
+---------------------------------------------------------+
1 row in set (0.00 sec)

mysql> SELECT WEEKOFYEAR( 1998-02-20 );
+---------------------------------------------------------+
| WEEKOFYEAR( 1998-02-20 )                                |
+---------------------------------------------------------+
| 8                                                       |
+---------------------------------------------------------+
1 row in set (0.00 sec)

mysql> SELECT YEAR( 98-02-03 );
+---------------------------------------------------------+
| YEAR( 98-02-03 )                                        |
+---------------------------------------------------------+
| 1998                                                    |
+---------------------------------------------------------+
1 row in set (0.00 sec)

mysql> SELECT YEARWEEK( 1987-01-01 );
+---------------------------------------------------------+
| YEAR( 98-02-03 )YEARWEEK( 1987-01-01 )                  |
+---------------------------------------------------------+
| 198653                                                  |
+---------------------------------------------------------+
1 row in set (0.00 sec)

mysql> CREATE TEMPORARY TABLE SALESSUMMARY (
   -> product_name VARCHAR(50) NOT NULL
   -> , total_sales DECIMAL(12,2) NOT NULL DEFAULT 0.00
   -> , avg_unit_price DECIMAL(7,2) NOT NULL DEFAULT 0.00
   -> , total_units_sold INT UNSIGNED NOT NULL DEFAULT 0
);
Query OK, 0 rows affected (0.00 sec)

mysql> INSERT INTO SALESSUMMARY
   -> (product_name, total_sales, avg_unit_price, total_units_sold)
   -> VALUES
   -> ( cucumber , 100.25, 90, 2);

mysql> SELECT * FROM SALESSUMMARY;
+--------------+-------------+----------------+------------------+
| product_name | total_sales | avg_unit_price | total_units_sold |
+--------------+-------------+----------------+------------------+
| cucumber     |      100.25 |          90.00 |                2 |
+--------------+-------------+----------------+------------------+
1 row in set (0.00 sec)

mysql> CREATE TEMPORARY TABLE SALESSUMMARY (
   -> product_name VARCHAR(50) NOT NULL
   -> , total_sales DECIMAL(12,2) NOT NULL DEFAULT 0.00
   -> , avg_unit_price DECIMAL(7,2) NOT NULL DEFAULT 0.00
   -> , total_units_sold INT UNSIGNED NOT NULL DEFAULT 0
);
Query OK, 0 rows affected (0.00 sec)

mysql> INSERT INTO SALESSUMMARY
   -> (product_name, total_sales, avg_unit_price, total_units_sold)
   -> VALUES
   -> ( cucumber , 100.25, 90, 2);

mysql> SELECT * FROM SALESSUMMARY;
+--------------+-------------+----------------+------------------+
| product_name | total_sales | avg_unit_price | total_units_sold |
+--------------+-------------+----------------+------------------+
| cucumber     |      100.25 |          90.00 |                2 |
+--------------+-------------+----------------+------------------+
1 row in set (0.00 sec)
mysql> DROP TABLE SALESSUMMARY;
mysql>  SELECT * FROM SALESSUMMARY;
ERROR 1146: Table  TUTORIALS.SALESSUMMARY  doesn t exist

SQL> SHOW CREATE TABLE TUTORIALS_TBL G; 
*************************** 1. row *************************** 
      Table: TUTORIALS_TBL 
Create Table: CREATE TABLE  TUTORIALS_TBL  ( 
   tutorial_id  int(11) NOT NULL auto_increment, 
   tutorial_title  varchar(100) NOT NULL default   , 
   tutorial_author  varchar(40) NOT NULL default   , 
   submission_date  date default NULL, 
  PRIMARY KEY  ( tutorial_id ), 
  UNIQUE KEY  AUTHOR_INDEX  ( tutorial_author ) 
) TYPE = MyISAM 
1 row in set (0.00 sec)

SQL> CREATE TABLE `CLONE_TBL` ( 
  ->  tutorial_id  int(11) NOT NULL auto_increment, 
  ->  tutorial_title  varchar(100) NOT NULL default   , 
  ->  tutorial_author  varchar(40) NOT NULL default   , 
  ->  submission_date  date default NULL, 
  -> PRIMARY KEY  (`tutorial_id ), 
  -> UNIQUE KEY  AUTHOR_INDEX  ( tutorial_author ) 
-> ) TYPE = MyISAM; 
Query OK, 0 rows affected (1.80 sec) 

SQL> INSERT INTO CLONE_TBL (tutorial_id, 
   ->                        tutorial_title, 
   ->                        tutorial_author, 
   ->                        submission_date) 
   -> SELECT tutorial_id,tutorial_title, 
   ->        tutorial_author,submission_date, 
   -> FROM TUTORIALS_TBL; 
Query OK, 3 rows affected (0.07 sec) 
Records: 3  Duppcates: 0  Warnings: 0 

SELECT column_name [, column_name ]
FROM   table1 [, table2 ]
WHERE  column_name OPERATOR
   (SELECT column_name [, column_name ]
   FROM table1 [, table2 ]
   [WHERE])

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

SQL> SELECT * 
   FROM CUSTOMERS 
   WHERE ID IN (SELECT ID 
         FROM CUSTOMERS 
         WHERE SALARY > 4500) ;

+----+----------+-----+---------+----------+
| ID | NAME     | AGE | ADDRESS | SALARY   |
+----+----------+-----+---------+----------+
|  4 | Chaitap |  25 | Mumbai  |  6500.00 |
|  5 | Hardik   |  27 | Bhopal  |  8500.00 |
|  7 | Muffy    |  24 | Indore  | 10000.00 |
+----+----------+-----+---------+----------+

INSERT INTO table_name [ (column1 [, column2 ]) ]
   SELECT [ *|column1 [, column2 ]
   FROM table1 [, table2 ]
   [ WHERE VALUE OPERATOR ]

SQL> INSERT INTO CUSTOMERS_BKP
   SELECT * FROM CUSTOMERS 
   WHERE ID IN (SELECT ID 
   FROM CUSTOMERS) ;

UPDATE table
SET column_name = new_value
[ WHERE OPERATOR [ VALUE ]
   (SELECT COLUMN_NAME
   FROM TABLE_NAME)
   [ WHERE) ]

SQL> UPDATE CUSTOMERS
   SET SALARY = SALARY * 0.25
   WHERE AGE IN (SELECT AGE FROM CUSTOMERS_BKP
      WHERE AGE >= 27 );

+----+----------+-----+-----------+----------+
| ID | NAME     | AGE | ADDRESS   | SALARY   |
+----+----------+-----+-----------+----------+
|  1 | Ramesh   |  35 | Ahmedabad |   125.00 |
|  2 | Khilan   |  25 | Delhi     |  1500.00 |
|  3 | kaushik  |  23 | Kota      |  2000.00 |
|  4 | Chaitap |  25 | Mumbai    |  6500.00 |
|  5 | Hardik   |  27 | Bhopal    |  2125.00 |
|  6 | Komal    |  22 | MP        |  4500.00 |
|  7 | Muffy    |  24 | Indore    | 10000.00 |
+----+----------+-----+-----------+----------+

DELETE FROM TABLE_NAME
[ WHERE OPERATOR [ VALUE ]
   (SELECT COLUMN_NAME
   FROM TABLE_NAME)
   [ WHERE) ]

SQL> DELETE FROM CUSTOMERS
   WHERE AGE IN (SELECT AGE FROM CUSTOMERS_BKP
      WHERE AGE >= 27 );

+----+----------+-----+---------+----------+
| ID | NAME     | AGE | ADDRESS | SALARY   |
+----+----------+-----+---------+----------+
|  2 | Khilan   |  25 | Delhi   |  1500.00 |
|  3 | kaushik  |  23 | Kota    |  2000.00 |
|  4 | Chaitap |  25 | Mumbai  |  6500.00 |
|  6 | Komal    |  22 | MP      |  4500.00 |
|  7 | Muffy    |  24 | Indore  | 10000.00 |
+----+----------+-----+---------+----------+

mysql> CREATE TABLE INSECT
   -> (
   -> id INT UNSIGNED NOT NULL AUTO_INCREMENT,
   -> PRIMARY KEY (id),
   -> name VARCHAR(30) NOT NULL, # type of insect
   -> date DATE NOT NULL, # date collected
   -> origin VARCHAR(30) NOT NULL # where collected
);
Query OK, 0 rows affected (0.02 sec)
mysql> INSERT INTO INSECT (id,name,date,origin) VALUES
   -> (NULL, housefly , 2001-09-10 , kitchen ),
   -> (NULL, milppede , 2001-09-10 , driveway ),
   -> (NULL, grasshopper , 2001-09-10 , front yard );
Query OK, 3 rows affected (0.02 sec)
Records: 3  Duppcates: 0  Warnings: 0
mysql> SELECT * FROM INSECT ORDER BY id;
+----+-------------+------------+------------+
| id | name        | date       | origin     |
+----+-------------+------------+------------+
|  1 | housefly    | 2001-09-10 | kitchen    |
|  2 | milppede   | 2001-09-10 | driveway   |
|  3 | grasshopper | 2001-09-10 | front yard |
+----+-------------+------------+------------+
3 rows in set (0.00 sec)

$dbh->do ("INSERT INTO INSECT (name,date,origin)
VALUES( moth , 2001-09-14 , windowsill )");
my $seq = $dbh->{mysql_insertid};

mysql_query ("INSERT INTO INSECT (name,date,origin)
VALUES( moth , 2001-09-14 , windowsill )", $conn_id);
$seq = mysql_insert_id ($conn_id);

mysql> ALTER TABLE INSECT DROP id;
mysql> ALTER TABLE insect
   -> ADD id INT UNSIGNED NOT NULL AUTO_INCREMENT FIRST,
   -> ADD PRIMARY KEY (id);

mysql> CREATE TABLE INSECT
   -> (
   -> id INT UNSIGNED NOT NULL AUTO_INCREMENT = 100,
   -> PRIMARY KEY (id),
   -> name VARCHAR(30) NOT NULL, # type of insect
   -> date DATE NOT NULL, # date collected
   -> origin VARCHAR(30) NOT NULL # where collected
);

mysql> ALTER TABLE t AUTO_INCREMENT = 100;

SELECT DISTINCT column1, column2,.....columnN 
FROM table_name
WHERE [condition]

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

SQL> SELECT SALARY FROM CUSTOMERS
   ORDER BY SALARY;

+----------+
| SALARY   |
+----------+
|  1500.00 |
|  2000.00 |
|  2000.00 |
|  4500.00 |
|  6500.00 |
|  8500.00 |
| 10000.00 |
+----------+

SQL> SELECT DISTINCT SALARY FROM CUSTOMERS
   ORDER BY SALARY;

+----------+
| SALARY   |
+----------+
|  1500.00 |
|  2000.00 |
|  4500.00 |
|  6500.00 |
|  8500.00 |
| 10000.00 |
+----------+

if (preg_match("/^w{8,20}$/", $_GET[ username ], $matches)) {
   $result = mysql_query("SELECT * FROM CUSTOMERS 
      WHERE name = $matches[0]");
} else {
   echo "user name not accepted";
}

// supposed input
$name = "Qadir ; DELETE FROM CUSTOMERS;";
mysql_query("SELECT * FROM CUSTOMSRS WHERE name= {$name} ");

if (get_magic_quotes_gpc()) {
   $name = stripslashes($name);
}
$name = mysql_real_escape_string($name);
mysql_query("SELECT * FROM CUSTOMERS WHERE name= {$name} ");

$sub = addcslashes(mysql_real_escape_string("%str"), "%_");
// $sub == \%str\_
mysql_query("SELECT * FROM messages 
   WHERE subject LIKE  {$sub}% ");