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1.
SQL - Overview
SQL
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) like 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, libraries &
pre-compilers.
Allows users to create and drop databases and tables.
Allows users to create view, stored procedure, functions in a database.
Allows users to set permissions on tables, procedures and views.
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 R elational Software which
later came to be known as Oracle.
1
SQL
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 a re –
Query Dispatcher
Optimization Engines
Classic Query Engine
SQL Query Engine, et c.
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 a re CREATE, SELECT,
INSERT, UPDATE, DELETE and DROP.
These commands can be classified into the following
groups based on their nature:
2
SQL
DDL - Data Definition Language
Command Description
CREATE Creates a new table, a view of a table, or other object in the
database.
ALTER Modifies an existing database object, such as a table.
DROP Deletes an entire table, a view of a ta ble or other objects in the
database.
DML - Data Manipulation Language
Command Description
SELECT Retrieves certain records from one or more tables.
INSERT Creates a record.
UPDATE Modifies records.
DELETE Deletes records.
DCL - Data Control Language
Command Description
GRANT Gives a privilege to user.
REVOKE Takes back privileges granted from user.
3
2.
SQL - RDBMS Concepts
SQL
What is RDBMS?
RDBMS stands for
R
elational
D
atabase
M
anagement
S
ystem.
RDBMS is the basis for SQL,
and for all modern dat abase systems like MS SQL Server, IBM DB2, Oracle, MySQL, and
Microsoft Access.
A Relational database ma nagement 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 | Chaitali | 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 individual 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:
4
SQL
+----+----------+-----+-----------+----------+
| 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 ADDR ESS, 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 limit the
type of data that can go into a table.
This ensures the accuracy and reliability of the data
in the database.
Constraints can either be column level or table level.
Column level const raints are applied
only to one column whereas, table level constraints are applied to the entire table.
Following are some of the most commonly used constraints available in SQL:
5
SQL
NOT NULL Constraint
: Ensures that a column cannot have a NULL value.
DEFAULT Const raint
: 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 C onstraint
: The CHECK constraint ensures that all values in a column satisfy
certain conditions.
INDEX
: Used to create and ret rieve data from t he database very quickly.
Data Integrity
The following categories of data integrity exist with each RDBMS:
Entity Integrity:
There are no duplicate rows in a table.
Domain Integrity:
Enforces valid 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 Normalization
Database normalization is the process of efficiently organizing data in a database.
There
are two reasons of this normalization process:
Eliminating 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.
Normalization consists of a series of
guidelines that help guide you in creating a good database structure.
Normalization guidelines are divided into normal forms; think of a form as the format or
the way a databa se structure is laid out.
The aim of normal forms is to organize the
database structure , so that it complies 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)
6
SQL
Database – First Normal Form (1NF)
The First normal form (1NF) sets basic rules for an organized database:
Define the data items required, because they become the columns in a table.
Place the related data items in a table.
Ensure that there are no repeating groups of data.
Ensure that there is a primary key.
First Rule of 1NF
You must define the data items.
This means looking at the data to be stored, organizing
the data into columns, defining what type of data each column contains and then finally
putting the related columns into their own table.
For example, you put all the columns relating to locations of meetings in the Location
table, those relating to members in the MemberDetails table and so on.
Second Rule of 1NF
The next step is ensuring that there are no repeating groups of data .
Consider we have
the following table:
CREATE TABLE CUSTOMERS(
ID INT NOT NULL,
NAME VARCHAR (20) NOT NULL,
AGE INT NOT NULL,
ADDRESS CHAR (25),
ORDERS VARCHAR(155)
);
So, if we populate this table for a single customer having multiple orders, then it would be
something as shown below:
ID NAME AGE ADDRESS ORDERS
100 Sachin 36 Lower West Side Cannon XL-200
100 Sachin 36 Lower West Side Battery XL-200
100 Sachin 36 Lower West Side Tripod Large
But as per the 1NF, we need to ensure that there are no repeating groups of data.
So, let
us break the above table into two parts and then join them using a key as shown in the
following program:
7
SQL
CUSTOMERS Table
CREATE TABLE CUSTOMERS(
ID INT NOT NULL,
NAME VARCHAR (20) NOT NULL,
AGE INT NOT NULL,
ADDRESS CHAR (25),
PRIMARY KEY (ID)
);
This table would have the following record:
ID NAME AGE ADDRESS
100 Sachin 36 Lower West Side
ORDERS Table
CREATE TABLE ORDERS(
ID INT NOT NULL,
CUSTOMER_ID INT NOT NULL,
ORDERS VARCHAR(155),
PRIMARY KEY (ID)
);
This table would have the following records:
ID CUSTOMER_ID ORDERS
10 100 Cannon XL-200
11 100 Battery XL-200
12 100 Tripod Large
Third Rule of 1NF
The final rule of the first normal form, create a primary key for each table which we have
already created.
8
SQL
Database – Second Normal Form (2NF)
The Second Normal Form states that it should meet all the rules for 1NF and there must
be no partial dependences of any of the columns on the primary key:
Consider a customer-order relation and you want to store customer ID, customer name,
order ID and order detail and the date of purchase:
CREATE TABLE CUSTOMERS(
CUST_ID INT NOT NULL,
CUST_NAME VARCHAR (20) NOT NULL,
ORDER_ID INT NOT NULL,
ORDER_DETAIL VARCHAR (20) NOT NULL,
SALE_DATE DATETIME,
PRIMARY KEY (CUST_ID, ORDER_ID)
);
This table is in the first normal form; in that it obeys all the rules of the first normal form.
In this table, the primary key consists of the CUST_ID and the ORDER_ID.
Combined, they
are unique assuming the same customer would hardly order the same thing.
However, the table is not in the second normal form because there are partial
dependencies of primary keys and columns.
CUST_NAME is dependent on CUST_ID and
there's no real link between a customer's name and what he purchased.
The order detail
and purchase date are also dependent on the ORDER_ID, but they are not dependent on
the CUST_ID, because there is no link between a CUST_ID and an ORDER_DETAIL or their
SALE_DATE.
To make this table comply with the second normal form, you need to separate the columns
into three tables.
First, create a table to store the customer details as shown in the code block below:
CREATE TABLE CUSTOMERS(
CUST_ID INT NOT NULL,
CUST_NAME VARCHAR (20) NOT NULL,
PRIMARY KEY (CUST_ID)
);
The next step is to create a table to store the details of each order:
CREATE TABLE ORDERS(
ORDER_ID INT NOT NULL,
ORDER_DETAIL VARCHAR (20) NOT NULL,
PRIMARY KEY (ORDER_ID)
);
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SQL
Finally, create a third table storing just the CUST_ID and the ORDER_ID to keep a track
of all the orders for a customer:
CREATE TABLE CUSTMERORDERS(
CUST_ID INT NOT NULL,
ORDER_ID INT NOT NULL,
SALE_DATE DATETIME,
PRIMARY KEY (CUST_ID, ORDER_ID)
);
Database – Third Normal Form (3NF)
A table is in a third normal form when the following conditions are met:
It is in the second normal form.
All non-primary fields are dependent on the primary key.
The dependency of these non-primary fields is between the data.
For example, in the
following table – the street name, city and the state are unbreakably bound to their zip
code.
CREATE TABLE CUSTOMERS(
CUST_ID INT NOT NULL,
CUST_NAME VARCHAR (20) NOT NULL,
DOB DATE,
STREET VARCHAR(200),
CITY VARCHAR(100),
STATE VARCHAR(100),
ZIP VARCHAR(12),
EMAIL_ID VARCHAR(256),
PRIMARY KEY (CUST_ID)
);
The dependency between the zip code and the address is called as a transitive dependency.
To comply with the third normal form, all you need to do is to move the Street, City and
the State fields into their own table, which you can call as the Zip Code table.
CREATE TABLE ADDRESS(
ZIP VARCHAR(12),
STREET VARCHAR(200),
CITY VARCHAR(100),
STATE VARCHAR(100),
PRIMARY KEY (ZIP)
);
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SQL
The next step is to alter the CUSTOMERS table as shown below.
CREATE TABLE CUSTOMERS(
CUST_ID INT NOT NULL,
CUST_NAME VARCHAR (20) NOT NULL,
DOB DATE,
ZIP VARCHAR(12),
EMAIL_ID VARCHAR(256),
PRIMARY KEY (CUST_ID)
);
The advantages of removing transitive dependencies are mainly two-fold.
First, the
amount of data duplication is reduced and therefore your database becomes smaller.
The second advantage is data integrity.
When duplicated data changes, there is a big risk
of updating only some of the data, especially if it is spread out in many different places in
the database.
For example, if the address and the zip code data were stored in three or four different
tables, then any changes in the zip codes would need to ripple out to every record in those
three or four tables.
11
3.
SQL - RDBMS Databases
SQL
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
May 1995.
rd
Windows Version was released on the 8
January 1998 for Windows 95 and NT.
th
Version 3.23: beta from June 2000, production release January 2001.
Version 4.0: beta from August 2002, production release March 2003 (unions).
Version 4.01: beta from August 2003, Jyoti adopts MySQL for database tracking.
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
February 2008.
th
Version 5.1: production release 27
November 2008.
th
Features
High Performance.
High Availability.
Scalability and Flexibility Run anything.
Robust Transactional Support.
Web and Data Warehouse Strengths.
Strong Data Protection.
Comprehensive Application Development.
12
SQL
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 clients.
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 Availability
Database mirroring
Database snapshots
CLR integration
Service Broker
DDL triggers
Ranking functions
Row version-based isolation levels
XML integration
TRY...CATCH
Database Mail
13
SQL
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 clients requesting and sending data in the network.
It is an excellent database server choice for client/server computing.
Oracle supports all
major operating systems for both clients 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 Ellison, 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
Softwa re 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 like concurrency
control - multi-version read consistency, etc.
1985 - Oracle version 4.0 was released.
It contained features like 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
Portability
Self-managing database
SQL*Plus
ASM
Scheduler
Resource Manager
14
SQL
Data Warehousing
Materialized 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 utilizes 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 easy-
to-use intuitive graphical interface.
1992 - Access version 1.0 was released.
1993 - Access 1.1 released to improve compatibility 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 application and data in one file.
This makes it very convenient to
distribute the entire application 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 like 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.
Unlike the client-server relational
database management systems (RDBMS), Microsoft Access does not implement
database triggers, stored procedures or transaction logging.
15
4.
SQL – Syntax
SQL
SQL is followed by a unique set of rules and guidelines called Syntax.
This tutorial gives
you a quick start with SQL by listing all the basic SQL Syntax.
All the SQL statements start with any of the keywords like SELECT, INSERT, UPDATE,
DELETE, ALTER, DROP, CREATE, USE, SHOW and all the statements end with a semicolon
(;).
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;
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SQL
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
17
SQL
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};
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SQL
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;
19
5.
SQL - Data Types
SQL
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 listed below -
Exact Numeric Data Types
DATA TYPE FROM TO
bigint -9,223,372,036,854,775,808 9,223,372,036,854,775,807
int -2,147,483,648 2,147,483,647
smallint -32,768 32,767
tinyint 0 255
bit 0 1
decimal -10^38 +1 10^38 -1
numeric -10^38 +1 10^38 -1
money -922,337,203,685,477.5808 +922,337,203,685,477.5807
smallmoney -214,748.3648 +214,748.3647
Approximate Numeric Data T ypes
DATA TYPE FROM TO
float -1.79E + 308 1.79E + 308
real -3.40E + 38 3.40E + 38
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SQL
Date and Time Data Types
DATA TYPE FROM TO
datetime Jan 1, 1753 Dec 31, 9999
smalldatetime Jan 1, 1900 Jun 6, 2079
date Stores a date like June 30, 1991
time Stores a time of day like 12:30 P.M.
Note
- Here, datetime has 3.33 milliseconds accuracy where as smalldatetime has 1
minute accura cy.
Character Strings Data T ypes
DATA TYPE Description
char Maximum length of 8,000 characters.( Fixed length non-
Unicode characters)
varchar Maximum of 8,000 characters.(Variable-length non-Unicode
data).
varchar(max) Maximum length of 231characters, Variable-length non-
Unicode data (SQL Server 2005 only).
text Variable-length non-Unicode data with a maximum length of
2,147,483,647 charact ers.
Unicode Character Strings Data Types
DATA TYPE Description
nchar Maximum length of 4,000 characters.( Fixed length Unicode)
nvarchar Maximum length of 4,000 characters.(Variable length Unicode)
nvarchar(max) Maximum length of 231chara cters (SQL Server 2005 only).(
Variable length Unicode)
21
SQL
ntext Maximum length of 1,073,741,823 cha racters.
( Variable length
Unicode )
Binary Data Types
DATA TYPE Descr iption
binary Maximum length of 8,000 bytes(Fixed-length binary data )
varbinary Maximum length of 8,000 bytes.(Variable length binary data)
varbinary(max) Maximum length of 231 bytes (SQL Server 2005 only).
(
Variable length Binary data)
image Maximum length of 2,147,483,647 bytes.
( Variable length
Binary Data)
Misc Data Types
DATA TYPE Description
sql_variant Stores values of va rious SQL Server-supported data types,
except text, ntext, and timestamp.
timestamp Stores a database-wide unique number that gets updated every
time a row gets updated
uniqueidentifier Stores a globally unique identifier (GUID)
xml Stores XML data.
You can store xml instances in a column or a
variable (SQL Server 2005 only).
cursor Reference to a cursor object
table Stores a result set for later processing
22
6.
SQL – Operators
SQL
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 operat ors
Operators used to negate conditions
SQL Arithmetic Operators
‘variable a’
‘variable b’
Assume
holds 10 and
holds 20, then:
Operator Description Example
+ Addition - Adds values on either side of the operator.
a + b will
give 30
a - b will
- Subtraction - Subtracts right hand operand from left hand
operand.
give -10
a * b will
* Multiplication - Multiplies values on either side of the
operator.
give 200
/ Division - Divides left hand operand by right hand operand.
b / a will
give 2
b % a will
% Modulus - Divides left hand operand by right hand operand
and returns remainder.
give 0
23
SQL
Arithmetic Operators – Examples
Here are a few simple examples showing the usage of SQL Arithmetic Operators:
Example 1:
SQL> select 10+ 20;
Output:
+--------+
| 10+ 20 |
+--------+
| 30 |
+--------+
1 row in set (0.00 sec)
Example 2:
SQL> select 10 * 20;
Output:
+---------+
| 10 * 20 |
+---------+
| 200 |
+---------+
1 row in set (0.00 sec)
Example 3:
SQL> select 10 / 5;
Output:
+--------+
| 10 / 5 |
+--------+
| 2.0000 |
+--------+
1 row in set (0.03 sec)
Example 4:
24
SQL
SQL> select 12 % 5;
Output:
+---------+
| 12 % 5 |
+---------+
| 2 |
+---------+
1 row in set (0.00 sec)
SQL Comparison Operators
‘variable a’
‘variable b’
Assume
holds 10 and
holds 20, then:
Operator Description Example
= Checks if the values of two operands are equal or not, if yes
(a = b) is
then condition becomes true.
not true.
!= Checks if the values of two operands are equal or not, if
(a != b) is
values are not equal then condition becomes true.
true.
<> Checks if the values of two operands are equal or not, if
(a <> b)
values are not equal then condition becomes true.
is true.
> Checks if the value of left operand is greater t han the value
(a > b) is
of right operand, if yes then condition becomes true.
not true.
< Checks if the value of left operand is less than the value of
(a < b) is
right operand, if yes then condition becomes true.
true.
>= Checks if the value of left operand is greater than or equal to
(a >= b)
the value of right operand, if yes then condition become s true.
is not
true.
25
SQL
<= Checks if the value of left operand is less than or equal to the
(a <= b)
value of right operand, if yes then condition becomes true.
is true.
!< Checks if the value of left operand is not less than the value
(a !< b) is
of right operand, if yes then condition becomes true.
false.
!> Checks if the value of left operand is not grea ter than the
(a !> b) is
value of right operand, if yes then condition becomes true.
true.
Comparison Operators – Examples
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 | Chaitali | 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)
Here are some simple examples showing the
usage of SQL Comparison Operators:
Example 1:
SQL> SELECT * FROM CUSTOMERS WHERE SALARY > 5000;
26
SQL
Output:
+----+----------+-----+---------+----------+
| ID | NAME | AGE | ADDRESS | SALARY |
+----+----------+-----+---------+----------+
| 4 | Chaitali | 25 | Mumbai | 6500.00 |
| 5 | Hardik | 27 | Bhopal | 8500.00 |
| 7 | Muffy | 24 | Indore | 10000.00 |
+----+----------+-----+---------+----------+
3 rows in set (0.00 sec)
Example 2:
SQL> SELECT * FROM CUSTOMERS WHERE SALARY = 2000;
Output:
+----+---------+-----+-----------+---------+
| ID | NAME | AGE | ADDRESS | SALARY |
+----+---------+-----+-----------+---------+
| 1 | Ramesh | 32 | Ahmedabad | 2000.00 |
| 3 | kaushik | 23 | Kota | 2000.00 |
+----+---------+-----+-----------+---------+
2 rows in set (0.00 sec)
Example 3:
SQL> SELECT * FROM CUSTOMERS WHERE SALARY != 2000;
Output:
+----+----------+-----+---------+----------+
| ID | NAME | AGE | ADDRESS | SALARY |
+----+----------+-----+---------+----------+
| 2 | Khilan | 25 | Delhi | 1500.00 |
| 4 | Chaitali | 25 | Mumbai | 6500.00 |
| 5 | Hardik | 27 | Bhopal | 8500.00 |
| 6 | Komal | 22 | MP | 4500.00 |
| 7 | Muffy | 24 | Indore | 10000.00 |
+----+----------+-----+---------+----------+
5 rows in set (0.00 sec)
27
SQL
Example 4:
SQL> SELECT * FROM CUSTOMERS WHERE SALARY <> 2000;
Output:
+----+----------+-----+---------+----------+
| ID | NAME | AGE | ADDRESS | SALARY |
+----+----------+-----+---------+----------+
| 2 | Khilan | 25 | Delhi | 1500.00 |
| 4 | Chaitali | 25 | Mumbai | 6500.00 |
| 5 | Hardik | 27 | Bhopal | 8500.00 |
| 6 | Komal | 22 | MP | 4500.00 |
| 7 | Muffy | 24 | Indore | 10000.00 |
+----+----------+-----+---------+----------+
5 rows in set (0.00 sec)
Example 5:
SQL> SELECT * FROM CUSTOMERS WHERE SALARY >= 6500;
Output:
+----+----------+-----+---------+----------+
| ID | NAME | AGE | ADDRESS | SALARY |
+----+----------+-----+---------+----------+
| 4 | Chaitali | 25 | Mumbai | 6500.00 |
| 5 | Hardik | 27 | Bhopal | 8500.00 |
| 7 | Muffy | 24 | Indore | 10000.00 |
+----+----------+-----+---------+----------+
3 rows in set (0.00 sec)
28
SQL
SQL Logical Operators
Here is a list of all the logical operators available in SQL.
Operator Description
ALL The ALL operator is used to compare a value to all values in another
value set.
AND The AND operator allows the existence of multiple conditions in an SQL
statement's WHERE clause.
ANY The ANY operator is used to compare a value to any applicable value in
the list as per the condition.
BETWEEN The BETWEEN operator is used to search for values that are within a set
of values, given the minimum value and the maximum value.
EXISTS The EXISTS operator is used to search for the presence of a row in a
specified table that meets a certain criterion.
IN The IN operator is used to compa re a value to a list of literal values that
have been specified.
LIKE The LIKE operator is used to compa re a value to similar values using
wildcard operators.
NOT The NOT operator reverses the meaning of the logical operator with
which it is used. Eg: NOT EXISTS, NOT BETWEEN, NOT IN, etc.
This is
a negate operator.
OR The OR operator is used to combine multiple conditions in an SQL
statement's WHERE clause.
IS NULL The NULL operator is used to compare a value with a NULL value.
29
SQL
UNIQUE The UNIQUE operator searches every row of a specified table for
uniqueness (no duplicates).
Logical Operators – Examples
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 | Chaitali | 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)
Here are some simple examples showing usage of SQL Comparison Operators:
Example 1:
SQL> SELECT * FROM CUSTOMERS WHERE AGE >= 25 AND SALARY >= 6500;
Output:
+----+----------+-----+---------+---------+
| ID | NAME | AGE | ADDRESS | SALARY |
+----+----------+-----+---------+---------+
| 4 | Chaitali | 25 | Mumbai | 6500.00 |
| 5 | Hardik | 27 | Bhopal | 8500.00 |
+----+----------+-----+---------+---------+
2 rows in set (0.00 sec)
30
SQL
Example 2:
SQL> SELECT * FROM CUSTOMERS WHERE AGE >= 25 OR SALARY >= 6500;
Output:
+----+----------+-----+-----------+----------+
| ID | NAME | AGE | ADDRESS | SALARY |
+----+----------+-----+-----------+----------+
| 1 | Ramesh | 32 | Ahmedabad | 2000.00 |
| 2 | Khilan | 25 | Delhi | 1500.00 |
| 4 | Chaitali | 25 | Mumbai | 6500.00 |
| 5 | Hardik | 27 | Bhopal | 8500.00 |
| 7 | Muffy | 24 | Indore | 10000.00 |
+----+----------+-----+-----------+----------+
5 rows in set (0.00 sec)
Example 3:
SQL> SELECT * FROM CUSTOMERS WHERE AGE IS NOT NULL;
Output:
+----+----------+-----+-----------+----------+
| ID | NAME | AGE | ADDRESS | SALARY |
+----+----------+-----+-----------+----------+
| 1 | Ramesh | 32 | Ahmedabad | 2000.00 |
| 2 | Khilan | 25 | Delhi | 1500.00 |
| 3 | kaushik | 23 | Kota | 2000.00 |
| 4 | Chaitali | 25 | Mumbai | 6500.00 |
| 5 | Hardik | 27 | Bhopal | 8500.00 |
| 6 | Komal | 22 | MP | 4500.00 |
| 7 | Muffy | 24 | Indore | 10000.00 |
+----+----------+-----+-----------+----------+
7 rows in set (0.00 sec)
31
SQL
Example 4:
SQL> SELECT * FROM CUSTOMERS WHERE NAME LIKE 'Ko%';
Output:
+----+-------+-----+---------+---------+
| ID | NAME | AGE | ADDRESS | SALARY |
+----+-------+-----+---------+---------+
| 6 | Komal | 22 | MP | 4500.00 |
+----+-------+-----+---------+---------+
1 row in set (0.00 sec)
Example 5:
SQL> SELECT * FROM CUSTOMERS WHERE AGE IN ( 25, 27 );
Output:
+----+----------+-----+---------+---------+
| ID | NAME | AGE | ADDRESS | SALARY |
+----+----------+-----+---------+---------+
| 2 | Khilan | 25 | Delhi | 1500.00 |
| 4 | Chaitali | 25 | Mumbai | 6500.00 |
| 5 | Hardik | 27 | Bhopal | 8500.00 |
+----+----------+-----+---------+---------+
3 rows in set (0.00 sec)
Example 6:
SQL> SELECT * FROM CUSTOMERS WHERE AGE BETWEEN 25 AND 27;
Output:
+----+----------+-----+---------+---------+
| ID | NAME | AGE | ADDRESS | SALARY |
+----+----------+-----+---------+---------+
| 2 | Khilan | 25 | Delhi | 1500.00 |
| 4 | Chaitali | 25 | Mumbai | 6500.00 |
| 5 | Hardik | 27 | Bhopal | 8500.00 |
+----+----------+-----+---------+---------+
3 rows in set (0.00 sec)
Example 7:
32
SQL
SQL> SELECT AGE FROM CUSTOMERS
WHERE EXISTS (SELECT AGE FROM CUSTOMERS WHERE SALARY > 6500);
Output:
+-----+
| AGE |
+-----+
| 32 |
| 25 |
| 23 |
| 25 |
| 27 |
| 22 |
| 24 |
+-----+
7 rows in set (0.02 sec)
Example 8:
SQL> SELECT * FROM CUSTOMERS
WHERE AGE > ALL (SELECT AGE FROM CUSTOMERS WHERE SALARY > 6500);
Output:
+----+--------+-----+-----------+---------+
| ID | NAME | AGE | ADDRESS | SALARY |
+----+--------+-----+-----------+---------+
| 1 | Ramesh | 32 | Ahmedabad | 2000.00 |
+----+--------+-----+-----------+---------+
1 row in set (0.02 sec)
Example 9:
33
SQL
SQL> SELECT * FROM CUSTOMERS
WHERE AGE > ANY (SELECT AGE FROM CUSTOMERS WHERE SALARY > 6500);
Output:
+----+----------+-----+-----------+---------+
| ID | NAME | AGE | ADDRESS | SALARY |
+----+----------+-----+-----------+---------+
| 1 | Ramesh | 32 | Ahmedabad | 2000.00 |
| 2 | Khilan | 25 | Delhi | 1500.00 |
| 4 | Chaitali | 25 | Mumbai | 6500.00 |
| 5 | Hardik | 27 | Bhopal | 8500.00 |
+----+----------+-----+-----------+---------+
4 rows in set (0.00 sec)
34
7.
SQL – Expressions
SQL
An expression is a combination of one or more values, operators and SQL functions that
evaluate to a value. These SQL EXPRESSIONs are like 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 SELEC T 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 | Chaitali | 25 | Mumbai | 6500.00 |
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SQL
| 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 Expressions
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 Nume ric Expressions:
SQL> SELECT (15 + 6) AS ADDITION
+----------+
| ADDITION |
+----------+
| 21 |
+----------+
1 row in set (0.00 sec)
There are several built-in functions like avg(), sum(), count(), etc., t o perform what is
known as the aggregate data calculations against a table or a specific table column.
36
SQL
SQL> SELECT COUNT(*) AS "RECORDS" FROM CUSTOMERS;
+---------+
| RECORDS |
+---------+
| 7 |
+---------+
1 row in set (0.00 sec)
Date Expressions
Date Expressions return the 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)
37
8.
SQL – CREATE Database
SQL
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 na me should be unique within the RDBMS.
Example
If you want to create a new database
