UNIT-3 Introduction to SQL · 2020-03-13 · UNIT-3 Introduction to SQL 3.1 Introduction SQL fully...

UNIT-3

Introduction to SQL

3.1 Introduction

SQL fully abbreviated as Structured Query Language can be defined as a domain-specific language used to manage the relational databases and performs different operations on the data stored in them. SQL is used as their standard database language by all the relational database management systems like Oracle, Informix, Posgres, SQL server, MySQL, MS Access, and Sybase.

3.1. 1 Characteristics of SQL SQL is easy to learn. SQL is used to access data from relational database management systems. SQL can execute queries against the database. SQL is used to describe the data. SQL is used to define the data in the database and manipulate it when needed. SQL is used to create and drop the database and table. SQL is used to create a view, stored procedure, function in a database. SQL allows users to set permissions on tables, procedures, and views.

3.1.2 Advantages of SQL: There are the following advantages of SQL: High speed: Using the SQL queries, the user can quickly and efficiently retrieve a large amount of records from a database. No coding needed: In the standard SQL, it is very easy to manage the database system. It doesn't require a substantial amount of code to manage the database system. Well defined standards: Long established are used by the SQL databases that are being used by ISO and ANSI. Portability: SQL can be used in laptop, PCs, server and even some mobile phones. Interactive language: SQL is a domain language used to communicate with the database. It is also used to receive answers to the complex questions in seconds. Multiple data view: Using the SQL language, the users can make different views of the database structure. 3.2 SQL DATA TYPE SQL Data type is used to define the values that a column can contain. Every column is required to have a name and data type in the database table. Different data types in SQL Are as follow.

1. Binary data types 2. Exact Numeric Data type 3. Approximate Numeric Data type 4. Character String Data type 5. Date and time Data type

1. Binary Data types: There are Three types of binary Datatypes which are given below

Database Management System Unit-3: Introduction to SQL

Prepared By: Mr. V. K. Wani 2

Data Type Description

Binary It has a maximum length of 8000 bytes. It contains fixed-length binary data.

varbinary It has a maximum length of 8000 bytes. It contains variable-length binary data.

Image It has a maximum length of 2,147,483,647 bytes.

2. Approximate Numeric Data type: The subtypes are given below:

Data type From To Description

float -1.79E + 308 1.79E + 308 It is used to specify a floating-point value e.g. 6.2, 2.9 etc.

real -3.40e + 38 3.40E + 38 It specifies a single precision floating point number

3. Exact Numeric Data type: The subtypes are given below:

Data type Description

int It is used to specify an integer value.

smallint It is used to specify small integer value.

bit It has the number of bits to store.

decimal It specifies a numeric value that can have a decimal number.

numeric It is used to specify a numeric value.

4. Character String Data type: The subtypes are given below:

Data type

Description

char It has a maximum length of 8000 characters. It contains Fixed-length non-unicode characters.

varchar It has a maximum length of 8000 characters. It contains variable-length non-unicode characters.

text It has a maximum length of 2,147,483,647 characters. It contains variable-length non-unicode characters.

5. Date and time Data type: The subtypes are given below:

Data type Description

date It is used to store the year, month, and days value.

time It is used to store the hour, minute, and second values.

timestamp It stores the year, month, day, hour, minute, and the second value.



What is MySQL: MySQL is a fast, easy to use relational database. It is currently the most popular open-source database. It is very commonly used in conjunction with PHP scripts to create powerful and dynamic server-side applications. MySQL is used for many small and big businesses. It is developed, marketed and supported by MySQL AB, a Swedish company. It is written in C and C++.

3.3 REASONS OF POPULARITY/ CHARACTERISTICS OF MYSQL: MySQL is becoming so popular because of these following reasons: MySQL is an open-source database so you don't have to pay a single penny to use it. MySQL is a very powerful program so it can handle a large set of functionality of the most expensive and powerful database packages. MySQL is customizable because it is an open source database and the open-source GPL license facilitates programmers to modify the SQL software according to their own specific environment. MySQL is quicker than other databases so it can work well even with the large data set. MySQL supports many operating systems with many languages like PHP, PERL, C, C++, JAVA, etc. MySQL uses a standard form of the well-known SQL data language. MySQL is very friendly with PHP, the most popular language for web development. MySQL supports large databases, up to 50 million rows or more in a table. The default file size limit for a table is 4GB, but you can increase this (if your operating system can handle it) to a theoretical limit of 8 million terabytes (TB).

3.4 MYSQL FEATURES

Relational Database Management System (RDBMS): MySQL is a relational database management system.

Easy to use: MySQL is easy to use. You have to get only the basic knowledge of SQL. You can build and interact with MySQL with only a few simple SQL statements.

It is secure: MySQL consist of a solid data security layer that protects sensitive data from intruders. Passwords are encrypted in MySQL.

Client/ Server Architecture: MySQL follows a client /server architecture. There is a database server (MySQL) and arbitrarily many clients (application programs), which communicate with the server; that is, they query data, save changes, etc.

Free to download: MySQL is free to use and you can download it from MySQL official website.

It is scalable: MySQL can handle almost any amount of data, up to as much as 50 million rows or more. The default file size limit is about 4 GB. However, you can increase this number to a theoretical limit of 8 TB of data.

Compatible on many operating systems: MySQL is compatible to run on many operating systems, like Novell NetWare, Windows* Linux*, many varieties of UNIX* (such as Sun* Solaris*, AIX, and DEC* UNIX), OS/2, FreeBSD*, and others. MySQL also provides a facility that the clients can run on the same computer as the server or on another computer.



Allows roll-back: MySQL allows transactions to be rolled back, commit and crash recovery.

High Performance: MySQL is faster, more reliable and cheaper because of its unique storage engine architecture.

High Flexibility: MySQL supports a large number of embedded applications which makes MySQL very flexible.

High Productivity: MySQL uses Triggers, Stored procedures and views which allows the developer to give a higher productivity.

3.4.1 Disadvantages / Drawback of MySQL: Following are the few disadvantages of MySQL: MySQL version less than 5.0 doesn't support ROLE, COMMIT and stored procedure. MySQL does not support a very large database size as efficiently. MySQL doesn't handle transactions very efficiently and it is prone to data corruption. MySQL is accused that it doesn't have a good developing and debugging tool compared to

paid databases. MySQL doesn't support SQL check constraints.

3.4.2 MySQL Data Types: A Data Type specifies a particular type of data, like integer, floating points, Boolean etc. It also identifies the possible values for that type, the operations that can be performed on that type and the way the values of that type are stored. MySQL supports a lot number of SQL standard data types in various categories. It uses many different data types broken into mainly three categories: numeric, date and time, and string types.

Numeric Data Type

Data Type Description

INT A normal-sized integer that can be signed or unsigned. If signed, the allowable range is from -2147483648 to 2147483647. If unsigned, the allowable range is from 0 to 4294967295. You can specify a width of up to 11 digits.

TINYINT A very small integer that can be signed or unsigned. If signed, the allowable range is from -128 to 127. If unsigned, the allowable range is from 0 to 255. You can specify a width of up to 4 digits.

SMALLINT A small integer that can be signed or unsigned. If signed, the allowable range is from -32768 to 32767. If unsigned, the allowable range is from 0 to 65535. You can specify a width of up to 5 digits.

MEDIUMINT A medium-sized integer that can be signed or unsigned. If signed, the allowable range is from -8388608 to 8388607. If unsigned, the allowable range is from 0 to 16777215. You can specify a width of up to 9 digits.

BIGINT A large integer that can be signed or unsigned. If signed, the allowable range is from -9223372036854775808 to 9223372036854775807. If unsigned, the allowable range is from 0 to 18446744073709551615. width up to 20 digits.

FLOAT(m,d) A floating-point number that cannot be unsigned. You can define the display length (m) and the number of decimals (d). This is not required and will default to 10,2, where 2 is the number of decimals and 10 is the total number



of digits. Decimal precision can go to 24 places for a float.

DOUBLE(m,d)

A double precision floating-point number that cannot be unsigned. You can define the display length (m) and the number of decimals (d). This is not required and will default to 16,4, where 4 is the number of decimals. Decimal precision can go to 53 places for a double. Real is a synonym for double.

DECIMAL(m,d) An unpacked floating-point number that cannot be unsigned. In unpacked decimals, each decimal corresponds to one byte. Defining the display length (m) and the number of decimals (d) is required.

Date and Time Data Type:

Data Type Maximum Size Explanation

DATE Range from '1000-01-01' to '9999-12-31'. Displayed as 'yyyy-mm-dd'.

DATETIME Values range from '1000-01-01 00:00:00' to '9999-12-31 23:59:59'.

Displayed as 'yyyy-mm-dd hh:mm:ss'.

TIMESTAMP(m) Values range from '1970-01-01 00:00:01' UTC to '2038-01-19 03:14:07' TC.

Displayed as 'YYYY-MM-DD HH:MM:SS'.

TIME Values range from '-838:59:59' to '838:59:59'. Displayed as 'HH:MM:SS'.

YEAR[(2|4)] Year value as 2 digits or 4 digits. Default is 4 digits.

String Data Types:

Data Type Maximum Size

CHAR(size) Maximum size of 255 characters.

VARCHAR(size) Maximum size of 255 characters.

TINYTEXT(size) Maximum size of 255 characters.

TEXT(size) Maximum size of 65,535 characters.

MEDIUMTEXT(size) Maximum size of 16,777,215 characters.

LONGTEXT(size) Max size of 4GB or 4,294,967,295 characters.

BINARY(size) Maximum size of 255 characters.

VARBINARY(size) Maximum size of 255 characters. Large Object Data Types (LOB) Data Types:

Data Type Syntax Maximum Size

TINYBLOB Maximum size of 255 bytes.

BLOB(size) Maximum size of 65,535 bytes.

MEDIUMBLOB Maximum size of 16,777,215 bytes.

LONGTEXT Maximum size of 4gb or 4,294,967,295 characters.



3.4.3 SQL Vs MySQL: SQL stands for Structured Query Language. It’s a standard language for accessing and manipulating databases. MySQL is a database management system, like SQL Server, Oracle, Informix, Postgres, etc. MySQL is an RDMS (Relational Database Management System). When considering a utility for data management the two most popular choices are MySQL and SQL Server. Both are efficient at keeping your data organized and readily available through a user interface. Both technologies have the concept of the schema (that is table storage) for data storage.

3.5 SQL OPERATOR 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. There are various types of SQL operator:

SQL Arithmetic Operators: Let's assume 'variable a' and 'variable b'. Here, 'a' contains 20 and 'b' contains 10.

Operator Description Example

+ It adds the value of both operands. a+b will give 30

- It is used to subtract the right-hand operand from the left-hand operand.

a-b will give 10

* It is used to multiply the value of both operands. a*b will give 200

/ It is used to divide the left-hand operand by the right-hand operand. a/b will give 2

% It is used to divide the left-hand operand by the right-hand operand and returns reminder.

a%b will give 0

SQL Comparison Operators: Let's assume 'variable a' and 'variable b'. Here, 'a' contains 20 and 'b' contains 10.

Operator Description Example

= It checks if two operands values are equal or not, if the values are queal then condition becomes true.

(a=b) is not true

!= It checks if two operands values are equal or not, if values are not (a!=b) is true



equal, then condition becomes true.

<> It checks if two operands values are equal or not, if values are not equal then condition becomes true.

(a<>b) is true

> It checks if the left operand value is greater than right operand value, if yes then condition becomes true.

(a>b) is not true

< It checks if the left operand value is less than right operand value, if yes then condition becomes true.

(a<b) is true

>= It checks if the left operand value is greater than or equal to the right operand value, if yes then condition becomes true.

(a>=b) is not true

<= It checks if the left operand value is less than or equal to the right operand value, if yes then condition becomes true.

(a<=b) is true

!< It checks if the left operand value is not less than the right operand value, if yes then condition becomes true.

(a!<b) is not true

!> It checks if the left operand value is not greater than the right operand value, if yes then condition becomes true.

(a!>b) is true

SQL Logical Operators: There is the list of logical operator used in SQL

Operator Description

ALL It compares a value to all values in another value set.

Some It compares a value to some values in another value set.

AND It allows the existence of multiple conditions in an SQL statement.

ANY It compares the values in the list according to the condition.

BETWEEN It is used to search for values that are within a set of values.

IN It compares a value to that specified list value.

NOT It reverses the meaning of any logical operator.

OR It combines multiple conditions in SQL statements.

EXISTS It is used to search for the presence of a row in a specified table.

LIKE It compares a value to similar values using wildcard operator.

IS NULL The NULL operator is used to compare a value with a NULL value.

UNIQUE The UNIQUE operator searches every row of a specified table for uniqueness (no duplicates).

3.6 SQL COMMAND

SQL commands are instructions. It is used to communicate with the database. It is also used to perform specific tasks, functions, and queries of data. SQL can perform various tasks like create a table, add data to tables, drop the table, modify the table, set permission for users.



Structured Query Language(SQL) as we all know is the database language by the use of which we can perform certain operations on the existing database and also we can use this language to create a database. SQL uses certain commands like Create, Drop, Insert etc. to carry out the required tasks. These SQL commands are mainly categorized into four categories as discussed below:

3.6.1 DDL (Data Definition Language) : DDL or Data Definition Language actually consists of the SQL commands that can be used to define the database schema. It simply deals with descriptions of the database schema and is used to create and modify the structure of database objects in database.

1. CREATE – is used to create the database or its objects (like table, index, function, views, store procedure and triggers). Syntax:

CREATE TABLE TABLE_NAME (COLUMN_NAME DATATYPES[,....]); Example: CREATE TABLE EMPLOYEE(Name VARCHAR2(20), Email VARCHAR2(100), DOB DATE);

2. DROP – is used to delete objects from the database. Syntax

DROP TABLE ; Example

DROP TABLE EMPLOYEE;

3. TRUNCATE–is used to remove all records from a table, including all spaces allocated for the records are removed, it does not disturb the structure of table, i.e after truncate your table with all attributes will be exist but all the rows in table will be deleted. Syntax:

TRUNCATE TABLE table_name; Example:

TRUNCATE TABLE EMPLOYEE;



4. COMMENT –is used to add comments to the data dictionary. This is similar to comment we add in program block.

/* add comment here*/

5. RENAME –is used to rename an objects like database, tables, views etc. existing in the database.

Syntax: Rename Object old_name to new_name; Example: Rename table emp to employee;

6. ALTER-is used to alter the structure of the table, It is used to alter the structure of the table. This change could be either to modify the characteristics of an existing attribute or probably to add a new attribute or to remove the existing attributes. Syntax:

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

ALTER TABLE table_name ADD (column_name datatype);

ALTER TABLE command to DROP COLUMN in an existing table is as follows.

ALTER TABLE table_name DROP COLUMN column_name;

ALTER TABLE command to RENAME ATTRIBUTE in an existing table is as follows.

ALTER TABLE table_name Rename old-column_name to new-column-name;

ALTER TABLE command to change the DATA TYPE of a column in a table is as follows.

ALTER TABLE table_name MODIFY (column_name datatype);

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;

ALTER TABLE to ADD UNIQUE CONSTRAINT to a table is as follows. ALTER TABLE table_name ADD CONSTRAINT MyUniqueConstraint UNIQUE(column1, column2...);

ALTER TABLE command to ADD CHECK CONSTRAINT to a table is as follows.

ALTER TABLE table_name ADD CONSTRAINT MyUniqueConstraint CHECK (CONDITION);

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...);

ALTER TABLE command to DROP CONSTRAINT from a table is as follows.

ALTER TABLE table_name DROP CONSTRAINT MyUniqueConstraint;

3.6.2 DML (Data Manipulation Language) : The SQL commands that deals with the manipulation of data present in database belong to DML or Data Manipulation Language and this includes most of the SQL statements.



1. SELECT – is Data Manipulation Language command used to retrieve data from the tables of selected database. It retrieves the data and displays the retrieved data on console. Syntax:

SELECT expressions FROM TABLES WHERE conditions; For example:

SELECT emp_name FROM employee WHERE age > 20;

2. INSERT – is Data Manipulation Language command used to insert data into a table. It can insert a single record at a time in a table. Syntax: INSERT INTO TABLE_NAME (col1, col2, …... col N) VALUES (value1, value2, ….. valueN);

Or INSERT INTO TABLE_NAME VALUES (value1, value2, value3, .... valueN); For example:

INSERT INTO javatpoint (Author, Subject) VALUES ("Sonoo", "DBMS");

3. UPDATE – is Data Manipulation Language command used to update existing data within a table. It can modify the any values or attributes for the particular tuple or row based on specified condition. Syntax:

UPDATE table_name SET [column_name1= value1,...column_nameN = valueN] [WHERE CONDITION]

For example: UPDATE students SET User_Name = 'Sonoo' WHERE Student_Id = '3'

4. DELETE – is Data Manipulation Language command used to delete records from a database table. It deletes the one or more record from tables depends on a conditions. Syntax: DELETE FROM table_name [WHERE condition]; For example: DELETE FROM JBook WHERE Author="Sonoo";

3.6.3 DCL (Data Control Language) : DCL includes commands such as GRANT and REVOKE which mainly deals with the rights, permissions and other controls of the database system.

1. GRANT-gives user’s access privileges to database. It is also used to create a database user with some privileges.

Example GRANT SELECT, UPDATE ON MY_TABLE TO SOME_USER, ANOTHER_USER;

2. REVOKE-withdraw user’s access privileges given by using the GRANT command. Example:

REVOKE SELECT, UPDATE ON MY_TABLE FROM USER1, USER2; 3.6.4 TCL (transaction Control Language) : TCL commands deals with the transaction within the database. 1. COMMIT– commits a Transaction, is used to save all the transactions to the database. Syntax:

COMMIT; Example:



DELETE FROM CUSTOMERS WHERE AGE = 25; COMMIT;

2. ROLLBACK– rollbacks a transaction in case of any error occurs. Rollback command is used to undo transactions that have not already been saved to the database. It can rollback all transaction which are not yet committed. Syntax:

ROLLBACK; Example:

DELETE FROM CUSTOMERS WHERE AGE = 25; ROLLBACK;

3. SAVEPOINT–sets a savepoint within a transaction.

4. SET TRANSACTION–specify characteristics for the transaction. 3.7 VIEWS IN SQL Views in SQL are a virtual table. A view also contains rows and columns. They have their own existence in database But they don’t save any records in a view. To create the view, we can select the fields from one or more tables present in the database. A view can either have specific rows based on certain condition or all the rows of a table. we can add SQL functions, WHERE, and JOIN statements to a view and present the data as if the data were coming from one single table. Student_Detail Student_Marks 1. Creating view: A view can be created using the CREATE VIEW statement. We can create a view from a single table or multiple tables. Syntax:

CREATE VIEW view_name AS SELECT column1, column2.....FROM table_name WHERE condit

ion;

2. Creating View from a single table: In this example, we create a View named DetailsView

from the table Student_Detail.

CREATE VIEW DetailsView AS SELECT NAME, ADDRESS FROM Student_Details WHERE

STU_ID < 4;

Just like table query, we can query the view to view the data: SELECT * FROM DetailsView;

STU_ID NAME ADDRESS

1 Stephan Delhi

2 Kathrin Noida

3 David Ghaziabad

4 Alina Gurugram

STU_ID NAME MARKS AGE

1 Stephan 97 19

2 Kathrin 86 21

3 David 74 18

4 Alina 90 20

5 John 96 18



Output:

2. Creating View from multiple tables: View from multiple tables can be created by simply

include multiple tables in the SELECT statement.

Example, a view is created named MarksView from two tables Student_Detail and Student_Marks.

CREATE VIEW MarksView AS SELECT Student_Detail.NAME, Student_Detail.ADDRESS, Student_Marks.MARKS FROM Student_Detail, Student_Mark WHERE Student_Detail.NAME = Student_Marks.NAME;

To display data of View MarksView: SELECT * FROM MarksView;

NAME ADDRESS MARKS

Stephan Delhi 97

Kathrin Noida 86

David Ghaziabad 74

Alina Gurugram 90 4. Deleting View: A view can be deleted using the Drop View statement.

Syntax DROP VIEW view_name;

Example: To delete the View MarksView, we can do this as: DROP VIEW MarksView;

3.8 NESTED QUERY A Subquery or Inner query or a Nested query is a query within another SQL query and embedded within the WHERE clause. A subquery is used to return data that will be used in the main query as a condition to further restrict the data to be retrieved. Subqueries can be used with the SELECT, INSERT, UPDATE, and DELETE statements along with the operators like =, <, >, >=, <=, IN, BETWEEN, etc. sub queries can retrieve the data from single or multiple tables.

There are a few rules that subqueries must follow Subqueries must be enclosed within parentheses. A subquery can have only one column in the SELECT clause, unless multiple columns are in the main query for the subquery to compare its selected columns. An ORDER BY command cannot be used in a subquery, although the main query can use an ORDER BY. The GROUP BY command can be used to perform the same function as the ORDER BY in a subquery. Subqueries that return more than one row can only be used with multiple value operators such as the IN operator.

NAME ADDRESS

Stephan Delhi

Kathrin Noida

David Ghaziabad



The SELECT list cannot include any references to values that evaluate to a BLOB, ARRAY, CLOB, or NCLOB. A subquery cannot be immediately enclosed in a set function. The BETWEEN operator cannot be used with a subquery. However, the BETWEEN operator can be used within the subquery.

1. Sub queries with the SELECT Statement: Subqueries are most frequently used with the SELECT statement. The basic syntax is as follows

SELECT column_name [, column_name ] FROM table1 [, table2 ] WHERE column_name OPERATOR (SELECT column_name [, column_name ] FROM table1 [, table2 ] [WHERE]) Example: Consider the CUSTOMERS table having the following records –

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

Now, let us check the following subquery with a SELECT statement.

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

This would produce the following result.

ID NAME AGE ADDRESS SALARY 4 Chaitali 25 Mumbai 6500.00 5 Hardik 27 Bhopal 8500.00 7 Muffy 24 Indore 10000.00

3. Subqueries with the INSERT Statement: Sub queries also can be used with INSERT statements. The INSERT statement uses the data returned from the subquery to insert into another table. The selected data in the sub query can be modified with any of the character, date or number functions. The basic syntax is as follows.

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

Example: Consider a table CUSTOMERS_BKP with similar structure as CUSTOMERS table. Now to copy the complete CUSTOMERS table into the CUSTOMERS_BKP table, you can use the following syntax.

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



4. Subqueries with the UPDATE Statement: The subquery can be used in conjunction with the UPDATE statement. Either single or multiple columns in a table can be updated when using a subquery with the UPDATE statement. The basic syntax is as follows.

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

Example: Assuming, we have CUSTOMERS_BKP table available which is backup of CUSTOMERS table. The following example updates SALARY by 0.25 times in the CUSTOMERS table for all the customers whose AGE is greater than or equal to 27.

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

This would impact two rows and finally CUSTOMERS table would have the following records.

ID NAME AGE ADDRESS SALARY 1 Ramesh 35 Ahmedabad 2500.00 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

5. Subqueries with the DELETE Statement: The subquery can be used in conjunction with the DELETE statement like with any other statements mentioned above. The basic syntax is as follows.

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

Example: Assuming, we have a CUSTOMERS_BKP table available which is a backup of the CUSTOMERS table. The following example deletes the records from the CUSTOMERS table for all the customers whose AGE is greater than or equal to 27.

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

This would impact two rows and finally the CUSTOMERS table would have the following records.

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



3.9 SQL INDEX Indexes are special lookup tables. It is used to retrieve data from the database very fast. An Index is used to speed up select queries and where clauses. But it slow down the data input with insert and update statements. Indexes can be created or dropped without affecting the data. An index in a database is just like an index in the back of a book. For example: When you reference all pages in a book that discusses a certain topic, you first have to refer to the index, which alphabetically lists all the topics and then referred to one or more specific page numbers. An index is used for several different reasons. The main reason is to speed up querying so that you can get rows or sort rows faster. Another reason is to define a primary-key or unique index which will guarantee that no other columns have the same values.

First we need to understand how normal (without indexing) query runs. It basically traverse each rows one by one and when it finds the data it returns. Refer the following image.

So suppose query is to find 50 , it will have to read 49 records as a linear search. Refer the following image.

When we apply indexing, the query will quickly find out the data without reading each one of them just by eliminating half of the data in each traversal like a binary search. The mysql indexes are stored as B-tree where all the data are in leaf node.



Indexes are used to retrieve data from the database very fast. The users cannot see the indexes, they are just used to speed up searches/queries. Indexes in a database are analogous to indexes that you find in a book. If a book has an index, and I ask you to find a chapter in that book, you can quickly find that with the help of the index. On the other hand, if the book does not have an index, you will have to spend more time looking for the chapter by looking at every page from the start to the end of the book. In a similar fashion, indexes in a database can help queries find data quickly.

3.7.1 Clustered Index: A clustered index defines the order in which data is physically stored in a table. Table data can be sorted in only way, therefore, there can be only one clustered index per table. In SQL Server, the primary key constraint automatically creates a clustered index on that particular column.

Ex. CREATE DATABASE schooldb

CREATE TABLE student ( id INT PRIMARY KEY, name VARCHAR(50) NOT NULL, gender VARCHAR(50) NOT NULL, DOB datetime NOT NULL, total_score INT NOT NULL, city VARCHAR(50) NOT NULL) in the “student” table we have set primary key constraint on the “id” column. This automatically creates a clustered index on the “id” column. To see all the indexes on a particular table execute “sp_helpindex” stored procedure. This stored procedure accepts the name of the table as a parameter and retrieves all the indexes of the table. The following query retrieves the indexes created on student table.

USE schooldb EXECUTE sp_helpindex student 3.7.2 Non-Clustered Indexes: A non-clustered index doesn’t sort the physical data inside the table. In fact, a non-clustered index is stored at one place and table data is stored in another place. This is similar to a textbook where the book content is located in one place and the index is located in another. This allows for more than one non-clustered index per table. It is important to mention here that inside the table the data will be sorted by a clustered index. However, inside the non-clustered index data is stored in the specified order. The index contains column values on which the index is created and the address of the record that the column value belongs to. When a query is issued against a column on which the index is created, the database will first go to the index and look for the address of the corresponding row in the table. It will then go to that row address and fetch other column values. It is due to this additional step that non-clustered indexes are slower than clustered indexes. use schooldb CREATE NONCLUSTERED INDEX IX_tblStudent_Name ON student(name ASC) The above script creates a non-clustered index on the “name” column of the student table. The index sorts by name in ascending order. As we said earlier, the table data and index will be stored in different places. The table records will be sorted by a clustered index if there is one. The index will be sorted according to its definition and will be stored separately from the table.

1. Create Index statement: It is used to create an index on a table. It allows duplicate value.



Syntax: CREATE INDEX index_name ON table_name (column1, column2, ...);

Example: CREATE INDEX idx_name ON Persons (LastName, FirstName);

2. Unique Index statement: It is used to create a unique index on a table. It does not allow

duplicate value.

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

Example: CREATE UNIQUE INDEX websites_idx ON websites (site_name);

3. Drop Index Statement: It is used to delete an index in a table.

Syntax: DROP INDEX index_name;

Example: DROP INDEX websites_idx;

ALTER command to add and drop INDEX: There are four types of statements for adding indexes to a table. ALTER TABLE tbl_name ADD PRIMARY KEY (column_list) − This statement adds a PRIMARY KEY, which means that the indexed values must be unique and cannot be NULL.

ALTER TABLE tbl_name ADD UNIQUE index_name (column_list) − This statement creates an index for which the values must be unique (except for the NULL values, which may appear multiple times).

ALTER TABLE tbl_name ADD INDEX index_name (column_list)− This adds an ordinary index in which any value may appear more than once.

ALTER TABLE tbl_name ADD FULLTEXT index_name (column_list) − This creates a special FULLTEXT index that is used for text-searching purposes.

Displaying INDEX Information: You can use the SHOW INDEX command to list out all the indexes associated with a table 3.10 SQL CLAUSES Clauses are used to apply some condition or constraints on the query The following are the various SQL clauses:

1. Where Clause 2. Order By Clause 3. Group By Clause 4. Having Clause 5. Distinct Clause

3.10.1 MySQL WHERE Clause: MySQL WHERE Clause is used with SELECT, INSERT, UPDATE and DELETE clause to filter the results. It specifies a specific position where you have to do the operation. Syntax: WHERE conditions;

Conditions: It specifies the conditions that must be fulfilled for records to be selected.



SELECT * FROM officers WHERE address = 'Mau';

MySQL WHERE Clause with AND condition: In this example, we are retrieving data from the table "officers" with AND condition.

SELECT * FROM officers WHERE address = 'Lucknow' AND officer_id < 5;

3.10.2 ORDER BY: The ORDER BY clause sorts the result-set in ascending or descending order. It sorts the records in ascending order by default. DESC keyword is used to sort the records in descending order. Syntax: ELECT column1, column2 FROM table_name WHERE condition ORDER BY column1, column2... ASC|DESC;

Where ASC: It is used to sort the result set in ascending order by expression. DESC: It sorts

the result set in descending order by expression.

Example: Sorting Results in Ascending Order

SELECT * FROM CUSTOMER ORDER BY NAME;

Example: Sorting Results in Descending Order

SELECT * FROM CUSTOMER ORDER BY NAME DESC;

3.10.3 GROUP BY Clause: The MYSQL GROUP BY Clause is used to collect data from multiple records and group the result by one or more column. It is generally used in a SELECT statement. You can also use some aggregate functions like COUNT, SUM, MIN, MAX, AVG etc. on the grouped column.

Syntax: SELECT expression1, expression2,... expression_n, aggregate_function (expression) FROM tables [WHERE conditions] GROUP BY expression1, expression2, ... expression_n;

Parameters: expression1, expression2, ... expression_n: It specifies the expressions that are not encapsulated within an aggregate function and must be included in the GROUP BY clause. Aggregate function: It specifies a function such as SUM, COUNT, MIN, MAX, or AVG etc. tables: It specifies the tables, from where you want to retrieve the records. There must be at least one table listed in the FROM clause.

WHERE conditions: It is optional. It specifies the conditions that must be fulfilled for the records to be selected.

SQL GROUP BY statement is used to arrange identical data into groups. The GROUP BY statement is used with the SQL SELECT statement.

The GROUP BY statement follows the WHERE clause in a SELECT statement and precedes the ORDER BY clause.

The GROUP BY statement is used with aggregation function.

Syntax: ELECT column FROM table_name WHERE conditions GROUP BY column ORDER BY column

3.10.4 MySQL HAVING Clause: MySQL HAVING Clause is used with GROUP BY clause. It always returns the rows where condition is TRUE. Syntax:



SELECT expression1, expression2, ... expression_n, aggregate_function (expression) FROM ta

bles [WHERE conditions] GROUP BY expression1, expression2, ... expression_n HAVING cond

ition;

Parameters

Aggregate function: It specifies any one of the aggregate function such as SUM, COUNT, MIN,

MAX, or AVG.

expression1, expression2, ... expression_n: It specifies the expressions that are not

encapsulated within an aggregate function and must be included in the GROUP BY clause.

WHERE conditions: It is optional. It specifies the conditions for the records to be selected.

HAVING condition: It is used to restrict the groups of returned rows. It shows only those

groups in result set whose conditions are TRUE.

Execute the following query:

SELECT emp_name, SUM(working_hours) AS "Total working hours" FROM employees GROUP BY emp_name HAVING SUM(working_hours) > 5;

3.10. 5: MySQL Distinct Clause: MySQL DISTINCT clause is used to remove duplicate records from the table and fetch only the unique records. The DISTINCT clause is only used with the SELECT statement. Syntax:

SELECT DISTINCT expressions FROM tables [WHERE conditions];

Parameters

expressions: specify the columns or calculations that you want to retrieve.

tables: specify the name of the tables from where you retrieve records. There must be at least

one table listed in the FROM clause.

WHERE conditions: It is optional. It specifies the conditions that must be met for the records

to be selected.

Note:

If you put only one expression in the DISTINCT clause, the query will return the unique values for that expression.

If you put more than one expression in the DISTINCT clause, the query will retrieve unique combinations for the expressions listed.

In MySQL, the DISTINCT clause doesn't ignore NULL values. So if you are using the DISTINCT clause in your SQL statement, your result set will include NULL as a distinct value.

Use the following query: SELECT DISTINCT address FROM officers;

3.11 SET OPERATIONS: SQL supports few Set operations which can be performed on the table data. These are used to get meaningful results from data stored in the table, under different special conditions. Or The SQL Set



operation is used to combine the two or more SQL SELECT statements. Four different types of SET operations, are

1. UNION 2. UNION ALL 3. INTERSECT 4. MINUS

The First table, The Second table,

ID Name 1 Abhi

2 Adam 3.11.1 UNION Operation: UNION is used to combine the results of two or more SELECT statements. However it will eliminate duplicate rows from its resultset. In case of union, number of columns and datatype must be same in both the tables, on which UNION operation is being applied.

The result set table will look like,

ID NAME 1 abhi 2 adam 3 Chester

3.11.2 UNION ALL: This operation is similar to Union. But it also shows the duplicate rows.

The result set table will look like,

ID NAME 1 abhi 2 adam 2 adam 3 Chester

3.11.3 INTERSECT: Intersect operation is used to combine two SELECT statements, but it only returns the records which are common from both SELECT statements. In case of Intersect the number of columns and datatype must be same. But remember MySQL does not support INTERSECT operator.

The result set table will look like

ID NAME 2 adam

ID Name 2 adam 3 Chester

Select * from First Union Select * from Second

Select * from First Union All Select * from Second

Select * from First INTERSECT Select * from Second



3.11.4 MINUS: The Minus operation combines results of two SELECT statements and return only those in the final result, which belongs to the first set of the result.

The result set table will look like

3.12 SET MEMBERSHIP: To Check whether any

values is a member of some set or not set membership is used. In SQL set membership is used with IN and NOT IN operator which allows you to easily test if an expression matches any value in a list of values. The IN operator checks a value within a set of values separated by commas and retrieve the rows from the table which are matching. The IN returns 1 when the search value present within the range otherwise returns 0. Consider Example with Relations

SavingAccount(Laccno, SCust_Name, Balance) Loan Account (Laccno, LCust_Name, Balance)

1. Find list of all customer name which are having Loan account as well saving account

Select * from SavingAccount where SCust_Name IN (Select * from LoanAccount)

2. Find list of Customer Belonging to any ne of following city.

SELECT * FROM Customers WHERE Country IN ('Germany', 'France', 'UK');

3.13 SET COMPARISON: Set comparison is SQL is used to compare the values in two set. Using arithmetic comparison operator we can just compare two values but if we want to compare more than one elements of two sets then set comparison can be used with SOME and ALL operator. First we will understand how All and Some operatorwork. Remember SOME operator will match any element of Set A with SOME elements of Set B. and ALL Operator will match any element of Set A with ALL elements of Set B. Consider two Sets

X={100, 200, 300} And Y = {300, 400, 500}

Condition for Some Operator

Result for Some Operator

Condition for All Operator

Result for All Operator

A < SOME B TRUE A < ALL B TRUE A <= SOME B TRUE A <= ALL B TRUE A >= SOME B TRUE A >= ALL B FALSE A > SOME B FALSE A > ALL B FALSE

A <> SOME B TRUE A <> ALL B FALSE A = SOME B TRUE A = ALL B FALSE

Consider the example with following relations

Branch(bname, bcity, assets) 1. Find the name of all branches that have assets greater than those of some branches located in nashik.

ID NAME 2 adam

Select * from First MINUS Select * from Second



Select bname from branch where assets > SOME (Select assets from Branch where bcity=’Nashik’)

2. Find the name of all branches that have assets greater than those of ALL branches located in nashik.

Select bname from branch where assets > ALL (Select assets from Branch where bcity=’Nashik’)

3.14 SQL 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. A SQL Join statement is used to combine data or rows from two or more tables based on a common field between them.

Why SQL JOIN is used? If you want to access more than one table through a select statement. If you want to combine two or more table then SQL JOIN statement is used .it combines

rows of that tables in one table and one can retrieve the information by a SELECT statement.

The joining of two or more tables is based on common field between them. SQL INNER JOIN also known as simple join is the most common type of join. JOINS allow us to combine data from more than one table into a single result set. JOINS have better performance compared to sub queries INNER JOINS only return rows that meet the given criteria. OUTER JOINS can also return rows where no matches have been found. The unmatched

rows are returned with the NULL keyword.

Let us Discus Different types of Joins with two tables Order & Customer

1. INNER JOIN 2. LEFT JOIN 3. RIGHT JOIN 4. FULL JOIN

Table 1: Customer

customer_id first_name last_name address city 1 George Washington 3200 Mt Vernon Hwy Mount Vernon 2 John Adams 1250 Hancock St Quincy 3 Thomas Jefferson 931 Thomas Jefferson Pkwy Charlottesville 4 James Madison 11350 Constitution Hwy Orange 5 James Monroe 2050 James Monroe Parkway Charlottesville

Table 2: Order

order_id order_date amount customer_id 1 07/04/1776 $234.56 1 2 03/14/1760 $78.50 3 3 05/23/1784 $124.00 2



4 09/03/1790 $65.50 3 5 07/21/1795 $25.50 10

6 11/27/1787 $14.40 9

1. INNER JOIN: The INNER JOIN keyword selects all rows from both the tables as long as the condition satisfies. This keyword will create the result-set by combining all rows from both the tables where the condition satisfies i.e value of the common field will be same. Syntax: Select t1.attribute, t2.attribute from Table1 t1 INNER JOIN Table t2 ON t1.matching_Column= t2.matching_Column

The Output of This Query will be

first_name last_name order_date order_amount George Washington 07/4/1776 $234.56

John Adams 05/23/1784 $124.00 Thomas Jefferson 03/14/1760 $78.50 Thomas Jefferson 09/03/1790 $65.50

2. LEFT JOIN: it is also called as Left Outer Join. This join returns all the rows of the table on the left side of the join and matching rows for the table on the right side of join. The rows for which there is no matching row on right side, the result-set will contain null. LEFT JOIN is also known as LEFT OUTER JOIN. Syntax: Select t1.attribute, t2.attribute from Table1 t1 LEFT JOIN Table t2 ON t1.matching_Column= t2.matching_Column


first_name last_name order_date order_amount George Washington 07/04/1776 $234.56

John Adams 05/23/1784 $124.00 Thomas Jefferson 03/14/1760 $78.50 Thomas Jefferson 09/03/1790 $65.50 James Madison NULL NULL James Monroe NULL NULL

3. RIGHT JOIN: it is also called as Right Outer Join. RIGHT JOIN is similar to LEFT JOIN. This join returns all the rows of the table on the right side of the join and matching rows for the

Select c.first_name, c.last_name,o. order_date, o.order_amount from customers c inner join orders o on c.customer_id = o.customer_id

Select c.first_name, c.last_name,o. order_date, o.order_amount from customers c Left join orders o on c.customer_id = o.customer_id



table on the left side of join. The rows for which there is no matching row on left side, the result-set will contain null. RIGHT JOIN is also known as RIGHT OUTER JOIN. Syntax: Select t1.attribute, t2.attribute from Table1 t1 RIGHT JOIN Table t2 ON t1.matching_Column= t2.matching_Column


4. FULL JOIN: FULL JOIN creates the result-set by combining result of both LEFT JOIN and RIGHT JOIN. The result-set will contain all the rows from both the tables. The rows for which there is no matching, the result-set will contain NULL values. Syntax: Select t1.attribute, t2.attribute from Table1 t1 FULL JOIN Table t2 ON t1.matching_Column= t2.matching_Column


3.15 AGGREGATE FUNCTIONS: In database management an aggregate function is a function where the values of multiple rows are grouped together as input on certain criteria to form a single value of more significant meaning. Different aggregate functions are as follow.

first_name last_name order_date order_amount George Washington 07/04/1776 $234.56 Thomas Jefferson 03/14/1760 $78.50

John Adams 05/23/1784 $124.00 Thomas Jefferson 09/03/1790 $65.50

NULL NULL 07/21/1795 $25.50 NULL NULL 11/27/1787 $14.40

first_name last_name order_date order_amount George Washington 07/04/1776 $234.56 Thomas Jefferson 03/14/1760 $78.50

John Adams 05/23/1784 $124.00 Thomas Jefferson 09/03/1790 $65.50

NULL NULL 07/21/1795 $25.50 NULL NULL 11/27/1787 $14.40 James Madison NULL NULL James Monroe NULL NULL

Select c.first_name, c.last_name,o. order_date, o.order_amount from customers c Right join orders o on c.customer_id = o.customer_id

Select c.first_name, c.last_name,o. order_date, o.order_amount from customers c Full join orders o On c.customer_id = o.customer_id



1. COUNT Function: COUNT function is used to Count the number of rows in a database table. It can work on both numeric and non-numeric data types. It uses the COUNT(*) that returns the count of all the rows in a specified table. COUNT(*) considers duplicate and Null.

Example: SELECT COUNT(*) FROM PRODUCT_MAST;

2. SUM Function: Sum function is used to calculate the sum of all selected columns. It works on numeric fields only.

Example: SELECT SUM(COST) FROM PRODUCT_MAST;

3. AVG function: The AVG function is used to calculate the average value of the numeric type. AVG function returns the average of all non-Null values.

Example: SELECT AVG(COST) FROM PRODUCT_MAST;

4. MAX Function: MAX function is used to find the maximum value of a certain column. This function determines the largest value of all selected values of a column.

Example: SELECT MAX(RATE) FROM PRODUCT_MAST;

5. MIN Function: MIN function is used to find the minimum value of a certain column. This function determines the smallest value of all selected values of a column.

Example: SELECT MIN(RATE) FROM PRODUCT_MAST; 3.16 TUPLE VARIABLE: A tuple variable is variable that takes on tuples of a particular relation schema as values. That is, every value assigned to a given tuple variable has the same number and type of fields. Consider the Table

order_id order_date amount 1 07/04/1776 $234.56 2 07/04/1776 $78.50 3 05/23/1784 $124.00 4 05/23/1784 $65.50 5 07/21/1795 $25.50

6 11/27/1787 $14.40

order_date Sale_of_Day 07/04/1776 $313.06 05/23/1784 $189.50 07/21/1795 $25.50 11/27/1787 $14.40

Select Order_date, Sum(Amount) AS ‘Sale_of_Day ’ from order group by order_date.

The Output of this will look like this where as Sale_of_Day is a tuple variable.



3.17 ORDERING OF TUPLES: Ordering of tuple is the process of ordering the rows in a table in some order i.e. either ascending or descending order. This can be used with Order by clause. To arrange the rows in ascending order we use the symbol ASC and for arranging the rows in descending order we use DESC symbol along with order by clause. If we does not specify the order sequence then by default it will arrange the rows in ascending order. Example: Select * from Order ORDER BY order_id ASC; OR Select * from Order ORDER BY order_id DESC; 3.18 INTRODUCTION TO MONGODB: MongoDB was developed by Eliot Horowitz and Dwight Merriman in the year 2007, when they experienced some scalability issues with the relational database while developing enterprise web applications at their company DoubleClick. MongoDB is a NoSQL database which stores the data in form of key-value pairs. It is an Open Source, Document Database which provides high performance and scalability along with data modelling and data management of huge sets of data in an enterprise application. MongoDB also provides the feature of Auto-Scaling. Since, MongoDB is a cross platform database and can be installed across different platforms like Windows, Linux etc. What is Document based storage? : A Document is nothing but a data structure with name-value pairs like in JSON. It is very easy to map any custom Object of any programming language with a MongoDB Document. For example : Studentobject has attributes name, rollno and subject where subjects is a List { Name: ’ABCD’ Rollno: 1 Subject: [C, C++, JAVA, PYTHON] } What is NoSQL: NoSQL, is basically a database used to manage huge sets of unstructured data, where in the data is not stored in tabular relations like relational databases. Most of the currently existing Relational Databases have failed in solving some of the complex modern problems.

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