Database Design & System Analysis

Course of Database Design and

System Analysis

Database System

Databases• Database

– A database is a collection of data, typically describing the activities of one or more related organizations. For example, a university database might contain information about the following:

– Entities such as students, faculty, courses, and classrooms.

– Relationships between entities, such as students' enrollment in courses, faculty

– teaching courses, and the use of rooms for courses.

• Databases are useful– Many computing applications deal with large

amounts of information.– Database systems give a set of tools for storing,

searching and managing this information.

Introduction

• Data: refer to what actually stored in the database.• Field: Group of characters with specific meaning• Record: Logically connected fields that describe a

person, place, or thing• File: Collection of related records• Information: it refer to the meaning of that data as

understood by some users.• Single-User System: is a system in which at most one

user can access the database at any given time.• Multi-User System: is a system in which many users can

access the database at the same time.A major objective of Multi-User Systems is to allow each user

to behave as if he or she were working with a single-user system instead.

The data in the database will be both integrated and shared.

Database Management System(DBMS)

• Collection of interrelated data• Is a layer of software between the data as physically stored

and users of system• Manages very large amounts of data.• Set of programs to access the data • DBMS contains information about a particular enterprise

• Database Applications:– Banking: all transactions– Airlines: reservations, schedules– Universities: registration, grades– Sales: customers, products, purchases– Manufacturing: production, inventory, orders, supply chain– Human resources: employee records, salaries, tax

deductions• Databases touch all aspects of our lives

Database Management System

(DBMS)

Database Management System(DBMS)

Database

End users

Application Programs

Figure (1): Simplified Picture of a database system

Why Use a DBMS?

• Data independence and efficient access.• Reduced application development time.• Data integrity and security.• Uniform data administration.• Concurrent access, recovery from

crashes.

Database Models• Collection of logical constructs used to

represent data structure and relationships within the database

• Implementation Database Models– Hierarchical – Network – Relational

Hierarchical Database Model• Logically represented by an upside

down tree– Each parent can have many children– Each child has only one parent

Network Database Model• Each record can have multiple parents

– Composed of sets– Each set has owner record and member record– Member may have several owners

Relational Database Model

• Perceived by user as a collection of tables for data storage

• Tables are a series of row/column intersections

• Tables related by sharing common entity characteristic(s)

Relational Database Model (con’t.)

Data Models

• A data model is a collection of concepts for describing data.

• A schema is a description of a particular collection of data, using the given data model.

• The relational model of data is the most widely used model today.– Main concept: relation, basically a table with rows

and columns.– Every relation has a schema, which describes the

columns, or fields.

Levels of Abstraction• Many views, single

conceptual (logical) schema and physical schema.– Views describe how users

see the data.

– Conceptual schema defines logical structure

– Physical schema describes the files and indexes used.

Physical Schema

Conceptual Schema

View 1 View 2 View 3

Example: University Database• Conceptual schema:

– Students (sid: string, name: string, login: string, age: integer, gpa:real(

– Courses (cid: string, cname:string, credits:integer) – Enrolled (sid:string, cid:string, grade:string)

• Physical schema:– Relations stored as unordered files. – Index on first column of Students.

• External Schema (View): – Course_info(cid:string,enrollment:integer)

Instance of Students Relation

Students( sid: string, name: string, login: string ,age: integer, gpa: real(

sidname login age gpa53666Jonesjones@cs 18 3.4

53688Smithsmith@ee 18 3.253650Smithsmith@math 19 3.8

mailto:jones@cs

mailto:smith@ee

mailto:smith@math

The Entity-Relationship Model

Introduction to Entity-Relationship (E-R) Modeling

• Notation uses three main constructs– Data entities– Attributes– Relationships

• Entity-Relationship (E-R) Diagram– A detailed, logical representation of the

entities, associations and data elements for an organization or business

Entity-Relationship (E-R) Modeling

Key Terms• Entity

– A person, place, object, event or concept in the user environment about which the organization wishes to maintain data

– Represented by a rectangle in E-R diagrams• Entity Type

– A collection of entities that share common properties or characteristics

• Attribute– A named property or characteristic of an entity that is

of interest to an organization


Key Terms• Candidate keys and identifiers

– Each entity type must have an attribute or set of attributes that distinguishes one instance from other instances of the same type

– Candidate key• Attribute (or combination of attributes) that

uniquely identifies each instance of an entity type


Key Terms• Identifier

– A candidate key that has been selected as the unique identifying characteristic for an entity type1. Avoid using intelligent keys

– Selection rules for an identifier1. Choose a candidate key that will not change its value2. Choose a candidate key that will never be null3. Consider substituting single value surrogate keys for

large composite keys

Notation Guide

• ENTITY TYPE

• WEAK ENTITY TYPE

• RELATIONSHIP TYPE

• IDENTIFYING RELATIONSHIP TYPE

…Notation Guide

• ATTRIBUTE

• KEY ATTRIBUTE

• MULTIVALUED ATTRIBUTE

• DERIVED ATTRIBUTE

• COMPOSITE ATTRIBUTE

_____

. . .

E1 R E2

E1 R E21 N

E2(min,max)

…Notation Guide

• TOTAL PARTICIPATION OF E2 IN R

• CARDINALITY RATIO 1:N FOR E1:E2 IN R

• STRUCTURAL CONSTRAINT (min, max) ON PARTICIPATION OF E IN R (Alternative Notation)

R

ER Diagram Basics

Relationship

Attributes

Entity

Product

Keeps

Store

descrip

qty

price

pname

manager

Locations

snameEntity

Product

Keeps

Store

descrip

qty

price

pname

manager

Locations

sname

Entity

Real-world object distinguishable from other objects (e.g a student, car, job, subject, building ...)

• An entity is described using a set of attributes

– In the Company database, an employee’s car is of lesser importance– In the Department of Transportation’s registration database, cars may be the most important concept– In both cases, cars will be represented as entities; but with different levels of detail

Entity Sets

A collection of similar entities (e.g. all employees)• All entities in an entity set have the same set of

attributes• Each entity set has a key• Each attribute has a domain• Can map entity set to a relation easily

SSN NAME SAL321-23-3241 Kim 23,000645-56-7895 Jones 45,000

EMPLOYEES

Entity TypeDefines set of entities that have

the same attributes (e.g. EMPLOYEE)

• Each Entity Type is described by its NAME and attributes

• The Entity Type describes the “Schema” or “Intension” for a set of entities

• Collection of all entities of a particular entity type at a given point in time is called the “Entity Set” or “Extension” of an Entity Type

• Entity Type and Entity Set are customarily referred to by the same name

EMPLOYEE

salSSN

name

Notation

EMPLOYEE

salSSN

name

Notation

Attributes

• Key Attributes• Value Sets of Attributes• Null Valued Attributes• Attribute Types

– Composite Vs. Simple Attributes– Single-valued Vs. Multi-valued Attributes– Derived Vs. Stored Attributes

Notation

Key Attributes: Identifier

• Key (or uniqueness) constraints are applied to entity types

• Key attribute’s values are distinct for each individual entity in the entity set

• A key attribute has its name underlined inside the oval

• Key must hold for every possible extension of the entity type

• Multiple keys are possible

EMPLOYEE

SSN

Composite Vs. Simple AttributesComposite attributes can be divided into

smaller parts which represent simple attributes with independent meaning

• Simple Attribute: Aircraft-Type• Complex Attribute: Aircraft-Location

which is comprised of :Aircraft-LatitudeAircraft-LongitudeAircraft-Altitude

Notation

… There is no formal concept of “compositeattribute” in the relational model

Simple attributes can either be single-valuedor multi-valued• Single-valued: Gender = F Notation

• Multivalued: Degree = {BSc, MInfTech} Notation

… An “attribute” in the relational model is always single valued - Values are atomic!

Single Vs. Multivalued Attributes

Derived Vs. Stored Attributes

Some attribute values can be derived fromrelated attribute values:• Age ® Date - B-day• Y-Sal ® 12 * M-Sal

EMPLOYEE

M-salB-days Y-sal

Age

Notation

Derived Vs. Stored Attributes

• Some attribute values can be derived from attributed values of related entities

• total-value ® sum (qty * price)

Order

Item price

qty

Total-Value

Representing Attributes

• Parenthesis ( ) for composite attributes• Brackets { } for multi-valued attributes

Assume a person can have more than one residence and each residence can have multiple telephones

{AddressPhone ({ Phone ( AreaCode,PhoneNum ) }, Address (StreetAddresss (Number, Street, AptNo),

City,State,PostalCode) ) }

Example of Elements of E-R Model

Entity Sets Departments Professors Students Administrators

Attributes Name of Departments, Phone No., Address... Name, SSN, Address of Professors...

Relationship Students and Professors are under a certain

department Admin manage the campus/ departments

Key Definitions• Primary Key:

– One attribute whose value can uniquely identify a complete record (one row of data) within an entity.

• Composite Primary Key– A primary key that consists of two or more

attribute within an entity.• Foreign Key

– A copy of a primary key that exists in another entity for the purpose of forming a relationship between the entities involved.

Degrees of a Relationship

Man Woman

Customer Order

Course Subject

One-to-one (1:1)

One-to-many (1:n)

Many-to-many (n:m)

NOTE: Every many to many relationship consists of two one to many relationships working in opposite directions

1 M

1 1

M M

Degrees of relationship, alternative representation

Man Woman

Customer Order

Course Subject

One-to-one (1:1)

One-to-many (1:n)

Many-to-many (n:m)

NOTE: Every many to many relationship consists of two one to many relationships working in opposite directions

A person must own at least one car. A car doesn’t have to be owned by a person, but if it is, it is owned by at least one person. A person may own many cars.

Notation for optional attributes

CarPerson

mandatory relationshipoptional relationship

1 M

A Sample ER Diagram

A Student Record Entity Diagram

Student

Course Subject

Example of the 3 elements in E/R Diagram

Entity B

Relationship

Attribute

Entity C

Entity A

Attribute

Attribute

E-R Diagram : Examples

• Add some attributes to entities here• Courses may have another course as pre-requisite


• Add some attributes to entities here• Courses may have another course as pre-requisite

Relationship Degree

• The degree of a relationship type is the number of participating entity types– 2 entities: Binary Relationship 3 entities: Ternary Relationship n entities: N-ary Relationship– Same entity type could participate in multiple relationship types

Part

Supplier Supply Project

Employees

Departments

Works_In

Assigned_to

Ternary

Multiple

Binary

StarsStars-in

year

Studios

Movies

length

Title AddressName

ownsfileType

Name Address


Kinds of Constraints

What kind of constraints can be defined in the ER Model?

• Cardinality Constraints• Participation ConstraintsTogether called “Structural Constraints”

Constraints are represented byspecific notation in the ER diagram

• The “Cardinality Ratio” for a binary relationship specifies the number of relationship instances that an entity can participate in– Works-In is a binary relationship– Participating entities are DEPARTMENT : EMPLOYEE– One department can have Many employees - Cardinality Ratio is 1 : N

Employees

Works_In

Departments

Possible Cardinality Ratios

One-to-Many A film is directed by at most one director A director can direct any number of films

Directorid

name

Directed Film title

Director Directed Film

Many-to-Many A film is directed by any number of directors A director can direct any number of films

Directorid

name

Directed Film title


One-to-One A film is directed by at most one director A director can direct at most one film

Directorid

name

Directed Film title


Another Example

Personid

name

age

FatherOf

Where would you put the arrow?

father

child

Example Cardinality Constraints

How many Employees can work in a Department? One employee can work in only one departmentHow many Employees can be employed by a Department? One department can employ many employeesHow many managers can a department have? One department can have only one managerHow many departments can an employee manage? One employee can have manage only one department

Normalisation

Introduction

• Normalization: is the process of efficiently organizing

data in a database with two goals in mind.

• First goal: eliminate redundant data

– for example, storing the same data in more than one

table

• Second Goal: ensure data dependencies make sense

– for example, only storing related data in a table

Benefits of Normalization

• Less storage space

• Quicker updates

• Less data inconsistency

• Clearer data relationships

• Easier to add data

• Flexible Structure

Redundancy and Data Anomalies

Example: We have the following relation that contains staff and department details:

staffNo job dept dname citySL10 Salesman 10 Sales Stratford SA51 Manager 20 Accounts BarkingDS40 Clerk 20 Accounts BarkingOS45 Clerk 30 Operations Barking

Redundant data is where we have stored the same ‘information’ more than once. i.e., the redundant data could be removed without the loss of information.

Insert Anomaly: We can’t insert a dept without inserting a member of staff that works in that department

Update Anomaly: We could change the name of the dept that SA51 works in without simultaneously changing the dept that DS40 works in.

Deletion Anomaly: By removing employee SL10 we have removed all information pertaining to the Sales dept.

Such ‘redundancy’ could lead to the following ‘anomalies’

Repeating GroupsA repeating group is an attribute (or set of attributes) that can have more than one value for a primary key value.

Example: We have the following relation that contains staff and department details and a list of telephone contact numbers for each member of staff.

staffNo job dept dname city contact numberSL10 Salesman 10 Sales Stratford 018111777, 018111888, 079311122 SA51 Manager 20 Accounts Barking 017111777DS40 Clerk 20 Accounts BarkingOS45 Clerk 30 Operations Barking 079311555

Repeating Groups are not allowed in a relational design, since all attributes have to be ‘atomic’ - i.e., there can only be one value per cell in a table!

Functional Dependency

Formal Definition: Attribute B is functionally dependant upon attribute A (or a collection of attributes) if a value of A determines a single value of attribute B at any one time.

Formal Notation: A B This should be read as ‘A determines B’ or ‘B is functionally dependant on A’. A is called the determinant and B is called the object of the determinant.

staffNo job dept dname SL10 Salesman 10 SalesSA51 Manager 20 AccountsDS40 Clerk 20 AccountsOS45 Clerk 30 Operations

Example:

staffNo jobstaffNo deptstaffNo dnamedept dname

Functional Dependencies

Dependencies: Definitions

• Partial Dependency – when an non-key attribute is determined by a part, but not the whole, of a COMPOSITE primary key.

CUSTOMER

Cust_ID Name Order_ID

101 AT&T 1234

101 AT&T 156

125 Cisco 1250

Partial Dependency

Dependencies: Definitions• Transitive Dependency – when a non-key

attribute determines another non-key attribute.

EMPLOYEE

Emp_ID F_Name L_Name Dept_ID Dept_Name

111 Mary Jones 1 Acct

122 Sarah Smith 2 Mktg

Transitive Dependency

Example: Table 1

Title Author1 Author2 ISBN Subject Pages Publisher

Database System

Concepts

Abraham Silberschatz

Henry F. Korth

0072958863 MySQL, Computers

1168 McGraw-Hill

Operating System

Concepts


Henry F. Korth

0471694665 Computers 944 McGraw-Hill

Table 1 problems

• This table is not very efficient with storage. • This design does not protect data integrity.

• Third, this table does not scale well.

First Normal Form

• In our Table 1, we have two violations of First Normal Form:

• First, we have more than one author field, • Second, our subject field contains more

than one piece of information. With more than one value in a single field, it would be very difficult to search for all books on a given subject.

First Normal Table

• Table 2

Title Author ISBN Subject Pages Publisher

Database System Concepts


0072958863 MySQL 1168 McGraw-Hill

Database System Concepts

Henry F. Korth 0072958863 Computers 1168 McGraw-Hill

Operating System Concepts

Henry F. Korth 0471694665 Computers 944 McGraw-Hill

Operating System Concepts


0471694665 Computers 944 McGraw-Hill

• We now have two rows for a single book. Additionally, we would be violating the Second Normal Form…

• A better solution to our problem would be to separate the data into separate tables- an Author table and a Subject table to store our information, removing that information from the Book table:

Subject_ID Subject

1 MySQL

2 Computers

Author_ID Last Name First Name

1 Silberschatz Abraham

2 Korth Henry

ISBN Title Pages Publisher

0072958863 Database System Concepts

1168 McGraw-Hill

0471694665 Operating System Concepts

944 McGraw-Hill

Subject Table

Author Table

Book Table

• Each table has a primary key, used for joining tables together when querying the data. A primary key value must be unique with in the table (no two books can have the same ISBN number), and a primary key is also an index, which speeds up data retrieval based on the primary key.

• Now to define relationships between the tables

Relationships

ISBN Author_ID

0072958863 1

0072958863 2

0471694665 1

0471694665 2

ISBN Subject_ID

0072958863 1

0072958863 2

0471694665 2

Book_Author TableBook_Subject Table

Second Normal Form

• As the First Normal Form deals with redundancy of data across a horizontal row, Second Normal Form (or 2NF) deals with redundancy of data in vertical columns.

• As stated earlier, the normal forms are progressive, so to achieve Second Normal Form, the tables must already be in First Normal Form.

• The Book Table will be used for the 2NF example

2NF Table

Publisher_ID Publisher Name

1 McGraw-Hill

ISBN Title Pages Publisher_ID

0072958863 Database System Concepts

1168 1

0471694665 Operating System Concepts

944 1

Publisher Table

Book Table

2NF

• Here we have a one-to-many relationship between the book table and the publisher. A book has only one publisher, and a publisher will publish many books. When we have a one-to-many relationship, we place a foreign key in the Book Table, pointing to the primary key of the Publisher Table.

• The other requirement for Second Normal Form is that you cannot have any data in a table with a composite key that does not relate to all portions of the composite key.

Third Normal Form

• Third normal form (3NF) requires that there are no functional dependencies of non-key attributes on something other than a candidate key.

• A table is in 3NF if all of the non-primary key attributes are mutually independent

• There should not be transitive dependencies

Boyce-Codd Normal Form

• BCNF requires that the table is 3NF and only determinants are the candidate keys

Stages of Normalisation

Unnormalised (UDF)

First normal form(1NF)

Remove repeating groups

Second normal form(2NF)

Remove partial dependencies

Third normal form(3NF)

Remove transitive dependencies

Boyce-Codd normalform (BCNF)

Remove remaining functional dependency anomalies

Fourth normal form(4NF)

Remove multivalued dependencies

Fifth normal form(5NF)

Remove remaining anomalies

DISTRIBUTED DATABASE SYSTEM

DISTRIBUTED DATABASESWHAT IS A DISTRIBUTED DATABASE?

Distributed: Deals with Physical distribution of data over multiple sites.

A distributed database system is a collection of logically related databases that co-operate in a transparent manner.

DISTRIBUTED DATABASES Stores logically related database over

physically independent sites

• Reduced Communication Overhead Most data access is local, less expensive and performs better.

• Improved Processing Power Instead of one server handling the full database, we now have a collection of machines handling the same database. • Removal of Reliance on a Central Site If a server fails, then the only part of the system that is affected is the relevant local site. The rest of the system remains functional and available.

DISTRIBUTED DATABASESADVANTAGES

• Expandability It is easier to accommodate increasing the size of the global (logical) database.

• Local autonomy The database is brought nearer to its users. This can effect a cultural change as it allows potentially greater control over local data .

DISTRIBUTED DATABASESADVANTAGES

Homogeneous & Heterogeneous DDBMSs

Homogeneous: All sites use same DBMS product. Much easier to design and manage. Approach provides incremental growth Allows increased performance.

Heterogeneous: Sites may run different DBMS products, underlying data models. • Sites implemented their own databases-integration considered later. • Translations required to allow for

• Typical solution is to use gateways.

Homogeneous & Heterogeneous DDBMSs

• Different hardware. • Different DBMS products.• Different hardware and DBMS products.

DISTRIBUTED DATABASES Fragmentation

Why fragment?Usage:

- Apps work with views rather than entire relations.

Efficiency:- It’s more efficient if data is close to where it is frequently used.

Security:- Data not required by local applications is not stored at the local site.

Parallelism:- It is possible to run several ‘sub-queries’ in tandem.

DISTRIBUTED DATABASES Fragmentation

Four types of fragmentation:1. Horizontal2. Vertical3. Mixed4. Derived

DISTRIBUTED DATABASESHORIZONTAL DATA FRAGMENTATION

333.00STRATFORDKHAN456500.00BARKINGONO400340.14BARKINGGREEN350

23.17STRATFORDSMITH345200.00BARKINGGRAY324

1000.00STRATFORDJONES200

BALANCEBRANCHCUSTOMERACCOUNT

Horizontal Fragmentation: Consists of a Restriction on a Relation.

e.g., ( branch = ‘Stratford’ Account)

DISTRIBUTED DATABASESHORIZONTAL DATA FRAGMENTATION

STRATFORDSTRATFORDSTRATFORD

333.00KHAN45623.17SMITH345

1000.00JONES200

BALANCEBRANCHCUSTOMERACCT NO.

BARKINGBARKINGBARKING

500.00ONO400340.14GREEN350200.00GRAY324

BALANCEBRANCHCUSTOMERACCT NO.

STRATFORD BRANCH

BARKING BRANCH

DISTRIBUTED DATABASESVERTICAL DATA FRAGMENTATION

KJTR78KHA456T0208-500-5821STRATFORDKHAN456

ZZEE56GRA324S0208-545-7528BARKINGGRAY324

XXYY22JON200T0208-500-9000STRATFORDJONES200

PASSWORDLOGINPHONE NOSITENAMES#

Vertical Fragmentation: Consists of a Projection on a Relation.

e.g., ( S#, NAME, SITE, PHONE NO Student)

DISTRIBUTED DATABASESVERTICAL DATA FRAGMENTATION

STRATFORDBARKING

STRATFORD

KHAN456GRAY324

0208-500-5821

0208-545-7528

0208-500-9000JONES200

PHONE NO.SITENAMES#

KJTR78ZZEE56XXYY22

KHA456T456GRA324S324JON200T200

PASSWORDLOGIN-IDS#

STUDENT ADMINISTRATION

NETWORK ADMINISTRATION

•Horizontal Fragmentation

•Rows split : Sal > 20K

•Vertical Fragmentation

Columns split : Primary Key retained

Id Name Sal Dept100 A 10K D1200 B 20K D2300 C 30K D3

Id Name Sal Dept100 A 10K D1200 B 20K D2

Id Name Sal Dept300 C 30K D3

Id Name

100 A

200 B

300 C

Id Sal Dept100 10K D1

200 20K D2

300 30K D3

Structured Query Language SQL

Introduction to SQL

• SQL is a standard language for accessing and manipulating databases

• What is SQL?– SQL stands for Structured Query Language – SQL lets you access and manipulate databases – SQL is an ANSI (American National Standards

Institute) standard

What Can SQL do?

• SQL can execute queries against a database • SQL can retrieve data from a database • SQL can insert records in a database • SQL can update records in a database • SQL can delete records from a database • SQL can create new databases • SQL can create new tables in a database • SQL can create stored procedures in a database • SQL can create views in a database • SQL can set permissions on tables, procedures, and

views

SQL DML and DDL

• SQL can be divided into two parts: The Data Manipulation Language (DML) and the Data Definition Language (DDL)

• The query and update commands form the DML part of SQL:– SELECT - extracts data from a database – UPDATE - updates data in a database – DELETE - deletes data from a database – INSERT INTO - inserts new data into a database

SQL DML and DDL

• The DDL part of SQL permits database tables to be created or deleted. It also define indexes (keys), specify links between tables, and impose constraints between tables. The most important DDL statements in SQL are:– CREATE DATABASE - creates a new database – ALTER DATABASE - modifies a database – CREATE TABLE - creates a new table – ALTER TABLE - modifies a table – DROP TABLE - deletes a table – CREATE INDEX - creates an index (search key) – DROP INDEX - deletes an index

SQL SELECT Statement

• The SELECT statement is used to select data from a database.

• The result is stored in a result table, called the result-set.

• SQL SELECT Syntax SELECT column_name(s(

FROM table_nameand SELECT * FROM table_name

SQL SELECT Example The "Persons" table:

P_Id LastName FirstName Address City

1 Hansen Ola Timoteivn 10 Sandnes2 Svendson Tove Borgvn 23 Sandnes3 Pettersen Kari Storgt 20 Stavanger

Now we want to select the content of the columns named "LastName" and "FirstName" from the table above.

We use the following SELECT statement:

SELECT LastName, FirstName FROM Persons

The result-set will look like this:

LastName FirstNameHansen Ola

Svendson TovePettersen Kari

SELECT * Example

• Now we want to select all the columns from the "Persons" table.• We use the following SELECT statement:

SELECT * FROM Persons

Tip: The asterisk (*) is a quick way of selecting all columns!• The result-set will look like this:


1 Hansen Ola Timoteivn 10 Sandnes

2 Svendson Tove Borgvn 23 Sandnes

3 Pettersen Kari Storgt 20 Stavanger

SQL SELECT DISTINCT Statement • In a table, some of the columns may contain duplicate values. This is

not a problem, however, sometimes you will want to list only the different (distinct) values in a table.

• The DISTINCT keyword can be used to return only distinct (different) values.

• SQL SELECT DISTINCT Syntax SELECT DISTINCT column_name(s(

FROM table_name

• SELECT DISTINCT ExampleThe "Persons" table:





SQL SELECT DISTINCT Statement • Now we want to select only the distinct values from the

column named "City" from the table above.• We use the following SELECT statement: SELECT DISTINCT City FROM PersonsThe result-set will look like this:

CitySandnesStavanger

For numeric values:

This is correct:SELECT * FROM Persons WHERE Year=1965This is wrong:SELECT * FROM Persons WHERE Year='1965'

SQL WHERE Clause

• The WHERE clause is used to filter records.• The WHERE clause is used to extract only those records

that fulfill a specified criterion.

SQL WHERE Syntax

SELECT column_name(s)

FROM table_name

WHERE column_name operator value

WHERE Clause ExampleThe "Persons" table:





Now we want to select only the persons living in the city "Sandnes" from the table above.


SELECT * FROM PersonsWHERE City='Sandnes'

WHERE Clause ExampleThe result-set will look like this:




SQL uses single quotes around text values (most database systems will also accept double quotes).Although, numeric values should not be enclosed in quotes.For text values:

This is correct:SELECT * FROM Persons WHERE FirstName='Tove'This is wrong:SELECT * FROM Persons WHERE FirstName=Tove

SQL WHERE Clause

For numeric values:

This is correct:

SELECT * FROM Persons WHERE Year=1965

This is wrong:

SELECT * FROM Persons WHERE Year='1965'

Operators Allowed in the WHERE Clause

Operator Description

= Equal

<> Not equal

> Greater than

< Less than

>= Greater than or equal

<= Less than or equal

BETWEEN Between an inclusive range

LIKE Search for a pattern

IN If you know the exact value you want to return for at least one of the columns

SQL AND & OR Operators• The AND & OR operators are used to filter records

based on more than one condition.• The AND operator displays a record if both the first

condition and the second condition is true.• The OR operator displays a record if either the first

condition or the second condition is true.

• AND Operator Example





Now we want to select only the persons with the first name equal to "Tove" AND the last name equal to "Svendson":

SQL AND & OR Operators


SELECT * FROM Persons WHERE FirstName='Tove' AND LastName='Svendson‘




SQL AND & OR Operators• OR Operator Example

• Now we want to select only the persons with the first name equal to "Tove" OR the first name equal to "Ola":

• We use the following SELECT statement:

SELECT * FROM PersonsWHERE FirstName ='Tove'OR FirstName ='Ola‘



1 Hansen Ola Timoteivn 10

Sandnes


You can also combine AND and OR (use parenthesis to form complex expressions).Now we want to select only the persons with the last name equal to "Svendson" AND the first name equal to "Tove" OR to "Ola":


SELECT * FROM Persons WHERELastName='Svendson'AND (FirstName='Tove' OR FirstName='Ola')


P_Id LastName FirstName

Address City


Combining AND & OR

SQL ORDER BY Keyword

• The ORDER BY keyword is used to sort the result-set by a specified column.

• The ORDER BY keyword sort the records in ascending order by default.

• If you want to sort the records in a descending order, you can use the DESC keyword.

• SQL ORDER BY Syntax

SELECT column_name(s)FROM table_nameORDER BY column_name(s) ASC|DESC

ORDER BY Example





4 Nilsen Tom Vingvn 23 Stavanger

Now we want to select all the persons from the table above, however, we want to sort the persons by their last name.


SELECT * FROM Persons ORDER BY LastName

ORDER BY ExampleThe result-set will look like this:






ORDER BY DESC Example:

Now we want to select all the persons from the table above, however, we want to sort the persons descending by their last name.

ORDER BY ExampleWe use the following SELECT statement:

SELECT * FROM PersonsORDER BY LastName DESC







SQL INSERT INTO Statement

The INSERT INTO statement is used to insert new records in a table.The first form doesn't specify the column names where the data will be

inserted, only their values:

INSERT INTO table_name VALUES (value1, value2, value3,...)

The second form specifies both the column names and the values to be inserted:

INSERT INTO table_name (column1, column2, column3,...)VALUES (value1, value2, value3,...)

SQL INSERT INTO ExampleWe have the following "Persons" table





Now we want to insert a new row in the "Persons" table.

We use the following SQL statement:

INSERT INTO PersonsVALUES (4,'Nilsen', 'Johan', 'Bakken 2', 'Stavanger')

SQL INSERT INTO Example

The "Persons" table will now look like this:





4 Nilsen Johan Bakken 2 Stavanger

Insert Data Only in Specified Columns• It is also possible to only add data in specific columns.• The following SQL statement will add a new row, but only add

data in the "P_Id", "LastName" and the "FirstName" columns:

INSERT INTO Persons (P_Id, LastName, FirstName)VALUES (5, 'Tjessem', 'Jakob')

The "Persons" table will now look like this:






5 Tjessem Jakob

SQL UPDATE Statement• The UPDATE statement is used to update existing records in a

table.

• SQL UPDATE Syntax

UPDATE table_nameSET column1=value, column2=value2,...WHERE some_column=some_value

Note: Notice the WHERE clause in the UPDATE syntax. The WHERE clause specifies which record or records that should be updated. If you omit the WHERE clause, all records will be updated!

SQL UPDATE ExampleThe "Persons" table:

P_Id LastName FirstName Address City1 Hansen Ola Timoteivn 10 Sandnes2 Svendson Tove Borgvn 23 Sandnes3 Pettersen Kari Storgt 20 Stavanger4 Nilsen Johan Bakken 2 Stavanger5 Tjessem Jakob

Now we want to update the person "Tjessem, Jakob" in the "Persons" table.We use the following SQL statement:

UPDATE PersonsSET Address='Nissestien 67', City='Sandnes'WHERE LastName='Tjessem' AND FirstName='Jakob'

SQL UPDATE ExampleThe "Persons" table will now look like this:

P_Id LastName FirstName Address City1 Hansen Ola Timoteivn 10 Sandnes2 Svendson Tove Borgvn 23 Sandnes3 Pettersen Kari Storgt 20 Stavanger4 Nilsen Johan Bakken 2 Stavanger5 Tjessem Jakob Nissestien 67 Sandnes

SQL UPDATE WarningBe careful when updating records. If we had omitted the WHERE clause in the example above, like this:

UPDATE PersonsSET Address='Nissestien 67', City='Sandnes'

SQL UPDATE Example

The "Persons" table would have looked like this:


1 Hansen Ola Nissestien 67 Sandnes

2 Svendson Tove Nissestien 67 Sandnes

3 Pettersen Kari Nissestien 67 Sandnes

4 Nilsen Johan Nissestien 67 Sandnes

5 Tjessem Jakob Nissestien 67 Sandnes

SQL DELETE Statement

The DELETE statement is used to delete records in a table.

SQL DELETE Syntax

DELETE FROM table_nameWHERE some_column=some_value

Note: Notice the WHERE clause in the DELETE syntax. The WHERE clause specifies which record or records that should be deleted. If you omit the WHERE clause, all records will be deleted!

SQL DELETE Example

The "Persons" table:






5 Tjessem Jakob Nissestien 67 Sandnes

Now we want to delete the person "Tjessem, Jakob" in the "Persons" table.


DELETE FROM PersonsWHERE LastName='Tjessem' AND FirstName='Jakob'

SQL DELETE ExampleThe "Persons" table will now look like this:






Delete All RowsIt is possible to delete all rows in a table without deleting the table. This means that the table structure, attributes, and indexes will be intact:

DELETE FROM table_nameorDELETE * FROM table_name

Note: Be very careful when deleting records. You cannot undo this statement!

The AVG() FunctionThe AVG() function returns the average value of a numeric column.

SQL AVG() Syntax

SELECT AVG(column_name) FROM table_name

SQL AVG() ExampleWe have the following "Orders" table:

O_Id OrderDate OrderPrice Customer1 2008/11/12 1000 Hansen2 2008/10/23 1600 Nilsen3 2008/09/02 700 Hansen4 2008/09/03 300 Hansen5 2008/08/30 2000 Jensen6 2008/10/04 100 Nilsen

Now we want to find the average value of the "OrderPrice" fields.We use the following SQL statement:

SELECT AVG(OrderPrice) AS OrderAverage FROM Orders


OrderAverage950

Now we want to find the customers that have an OrderPrice value higher than the average OrderPrice value.


SELECT Customer FROM OrdersWHERE OrderPrice>(SELECT AVG(OrderPrice) FROM Orders)


CustomerHansenNilsenJensen

The AVG() Function

The COUNT() function returns the number of rows that matches a specified criteria.

(1) SQL COUNT(column_name) Syntax The COUNT(column_name) function returns the

number of values (NULL values will not be counted) of the specified column:

SELECT COUNT(column_name) FROM table_name

SQL COUNT() Function

SQL COUNT() Function

(2) SQL COUNT(*) Syntax The COUNT(*) function returns the number of records in a

table:

SELECT COUNT(*) FROM table_name

(3) SQL COUNT(DISTINCT column_name) SyntaxThe COUNT(DISTINCT column_name) function returns the

number of distinct values of the specified column:

SELECT COUNT(DISTINCT column_name) FROM table_name

(1) SQL COUNT(column_name) We have the following "Orders" table:

SQL COUNT() Function Example

O_Id OrderDate OrderPrice Customer1 2008/11/12 1000 Hansen2 2008/10/23 1600 Nilsen3 2008/09/02 700 Hansen4 2008/09/03 300 Hansen5 2008/08/30 2000 Jensen6 2008/10/04 100 Nilsen

Now we want to count the number of orders from "Customer Nilsen".


SELECT COUNT(Customer) AS CustomerNilsen FROM OrdersWHERE Customer='Nilsen'

SQL COUNT() Function ExampleThe result of the SQL statement above will be 2, because the customer

Nilsen has made 2 orders in total:

CustomerNilsen2

(2) SQL COUNT(*) ExampleIf we omit the WHERE clause, like this:

SELECT COUNT(*) AS NumberOfOrders FROM Orders


NumberOfOrders6

which is the total number of rows in the table.

SQL COUNT() Function Example(3) SQL COUNT(DISTINCT column_name) Example Now we want to count the number of unique customers in the

"Orders" table.We use the following SQL statement:

SELECT COUNT(DISTINCT Customer) AS NumberOfCustomers FROM Orders


NumberOfCustomers3

which is the number of unique customers (Hansen, Nilsen, and Jensen) in the "Orders" table.

SQL INNER JOIN KeywordThe INNER JOIN keyword return rows when there is at least one match in both tables.

SQL INNER JOIN Syntax

SELECT column_name(s)FROM table_name1INNER JOIN table_name2ON table_name1.column_name=table_name2.column_name

SQL INNER JOIN ExampleThe "Persons" table:

P_Id LastName FirstName Address City1 Hansen Ola Timoteivn 10 Sandnes2 Svendson Tove Borgvn 23 Sandnes3 Pettersen Kari Storgt 20 Stavanger

The "Orders" table:

O_Id OrderNo P_Id1 77895 3

2 44678 3

3 22456 1

4 24562 1

5 34764 15

SQL INNER JOIN KeywordNow we want to list all the persons with any orders.


SELECT Persons.LastName, Persons.FirstName, Orders.OrderNoFROM PersonsINNER JOIN OrdersON Persons.P_Id=Orders.P_IdORDER BY Persons.LastName


LastName FirstName OrderNo

Hansen Ola 22456Hansen Ola 24562

Pettersen Kari 77895Pettersen Kari 44678

The INNER JOIN keyword return rows when there is at least one match in both tables. If there are rows in "Persons" that do not have matches in "Orders", those rows will NOT be listed.

Date post:	05-Jun-2017
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