Special relational operations | Relational Model

SPECIAL RELATIONAL OPERATIONS

These includes operations like
 

1. Selection
2. Projection
3. Join
4. Division

1. Selection-To identify a set of tuples which is a part of a relation and to extract only these tuples out. The select operation selects tuples that satisfy a given predicate or condition. It is also known as restriction operation. 

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Relational Model | Relational calculas

RELATIONAL CALCULUS

Relational algebra is concerned with a procedural language in which the user has to write the steps or procedure to obtain the required result.In this the user is not concerned with the detail of how to obtain information.

         In relational calculus the user tell his requirement and the output is available without knowing the method about its retrieval.

a.) It is a non procedural language.

b.) This concept was first expressed by codd. It is based on the predicate calculus.

c.) It is a formal language used to symbolize local argument in mathematics.Proposition specifying a property consist of an expression that names an individual object and an other expression called the predicate,that stands for the property that an individual object possesses.

In relational calculus we can make the following operations

Example-Let x and y are preposition then we can build other preposition like

"Not x"

"x and y"

 "x or y"m and so on.

Consider the following statement

India is a country.

We can write it.

" is a country  (India)"

we can drop is a then preposition will be

" Country (India)"

Finally if we use symbols for both predicates and objects then we can rewrite the statement X (a).Lower case letter denotes the variables beginning letters {a,b,c......}denotes the constants.

Upper case letter denotes the predicate.

P{X} where X is the argument.

It can be categorized into 2 parts:-

1,) Tuple Oriented Relational calculus

2.) Domain Oriented Relational calculus.

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Relational Model | Integrity constraints over relation

INTEGRITY CONSTRAINTS OVER RELATION

INTRODUCTION

Database integrity refers to the validity and consistency of stored data. Integrity is usually expressed in terms of constraints, which are consistency rules that the database is not permitted to violate. Constraints may apply to each attribute or they may apply to relationships between tables.

Integrity constraints ensure that changes (update deletion, insertion) made to the database by authorized users do not result in a loss of data consistency. Thus, integrity constraints guard against accidental damage to the database.

EXAMPLE- A brood group must be ‘A’ or ‘B’ or ‘AB’ or ‘O’ only (can not any other values else).

TYPES OF INTEGRITY CONSTRAINTS

Various types of integrity constraints are-

1. Domain Integrity
2. Entity Integrity Constraint
3. Referential Integrity Constraint
4. Key Constraints

1. Domain Integrity- Domain integrity means the definition of a valid set of values for an attribute. You define data type, length or size, is null value allowed , is the value unique or not for an attribute ,the default value, the range (values in between) and/or specific values for the attribute. 

2. Entity Integrity Constraint- This rule states that in any database relation value of attribute of a primary key can't be null.

EXAMPLE- Consider a relation "STUDENT" Where "Stu_id" is a primary key and it must not contain any null value whereas other attributes may contain null value e.g  "Branch" in the following relation contains one null value.

Stu_id	Name	Branch
11255234	Aman	CSE
11255369	Kapil	ECE
11255324	Ajay
11255237	Raman	CSE
11255678	Aastha	ECE

3.Referential Integrity Constraint-It states that if a foreign key exists in a relation then either the foreign key value must match a primary key value of some tuple in its home relation or the foreign key value must be null.

The rules are:

1. You can't delete a record from a primary table if matching records exist in a related table.

2. You can't change a primary key value in the primary table if that record has related records.

3. You can't enter a value in the foreign key field of the related table that doesn't exist in the primary key of the primary table.

4. However, you can enter a Null value in the foreign key, specifying that the records are unrelated.

EXAMPLE-Consider 2 relations "stu" and "stu_1" Where "Stu_id " is the primary key in the "stu" relation and foreign key in the "stu_1" relation.

Relation "stu"

Stu_id	Name	Branch
11255234	Aman	CSE
11255369	Kapil	ECE
11255324	Ajay	ME
11255237	Raman	CSE
11255678	Aastha	ECE

Relation "stu_1"

Stu_id	Cource	Duration
11255234	B.TECH	4 years
11255369	B.TECH	4 years
11255324	B.TECH	4 years
11255237	B.TECH	4 years
11255678	B.TECH	4 years

Examples

Rule 1. You can't delete any of the rows in the ”stu­” relation  that are visible  since all the ”stu” are in use in the “stu_1” relation.

Rule 2. You can't change any of the ”Stu_id” in the “stu” relation since all the “Stu_id” are in use in the ”stu_1” relation.

Rule 3. The values that you can enter in the” Stu_id” field in the “stu_1” relation must be in the” Stu_id” field in the “stu” relation.

Rule 4 You can enter a null value in the "stu_1" relation if the records are unrelated.

4.Key Constraints- A Key Constraint is a statement that a certain minimal subset of the fields of a relation is a unique identifier for a tuple.

There are 4 types of  key constraints-

1. Candidate key.
2. Super key
3. Primary key
4. Foreign key

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Relational Model | ER to Relational model conversion

ER TO RELATIONAL MODEL CONVERSION

INTRODUCTION- In the E-R model, data is represented using entities, and relationships are defined between these entities. However, with the relational model, the entities and their relationships follow strict guidelines. Usually, an E-R model is first developed, and then it is transformed into a relational model.

RULES TO CONVERT  ER TO RELATIONAL MODEL CONVERSION-

•        Build a table for each entity set
•         Build a table for each relationship set if necessary (more on this later)

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Object based data model | Data model

OBJECT BASED DATA MODEL

DEFINITION:-

It uses the concept such as entities ,attributes and relationship.

What is an entity?- An Entity is the distinct object in the organization and that is to be represented in database.There are 2 types of entities.Strong and weak entity.Entity type that do not have any key attributes are known as weak entity type but regular entity type that have key attributes are known as strong entity.

What is an attribute?- An attribute is that which describe some aspect of the object that we wish to record.

Types of attributes:-

1. Single value attributes:- These are the attribute that have single value.

2. Composite attributes:- It composed of multiple components.e.g

3. Simple attributes:- It is an attribute that composed of a single component with an independent existence. These attributes can't be further sub-divided.e.g age,rollno.

4. Multi-valued attributes: It can hold multiple value for a single attribute. e.g phone no

TYPES OF OBJECT BASED DATA MODELS:-There are 4 types of Object based data models:-

1.) ER(entity relationship) model

2.) Object oriented ER model

3.) Semantic model

4.) Functional model

1.) ER MODEL(entity relationship model)(Top-down approach):-It is the graphical technique i.e. used to convert the requirements of the system to a graphical representation for easy understanding.It is a conceptual model that used the objects as entity, attributes and relationships.Its basic component is ER diagram.It is simple and easy to understand .It can be easily converted to other models.

ER NOTATIONS:-

HOW TO DESIGN AN ER DIAGRAM:- EG. BANKING SYSTEM

2.) OBJECT ORIENTED ER MODEL:-The object oriented data model extends the definition of an entity to include,not only the attributes that describe the state of the object but also the actions that are associated with the object,that is its behavior.The object is said to encapsulate both state and behavior.

3.) SEMANTIC MODEL:- It is used to express greater inter-dependencies among the entities of interest.These inter-dependencies enable the model to represent semantics of the data in DB.This class of data models is influenced by the work of artificial intelligence researches semantic data model. It is developed to organize and represent knowledge not data. In coming times,DBMS will be fully partially intelligent

4.)FUNCTIONAL MODEL:-It describes computation within system(How output is derived from input).

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Relationship and their types | Data models

RELATIONSHIPS AND RELATIONSHIP SETS

INTRODUCTION OF RELATIONSHIPS-

After two or more entities are identified and defined with attributes, the participants determine if a relationship exists between the entities. A relationship is any association,linkage, or connection between the entities of interest to the business; it is a two-directional, significant association between two entities, or between an entity and itself.Each relationship has a name, an optional (optional or mandatory), and a degree (how many).

A relationship is described in real terms.Relationship represents an association between two or more entities.Entities enrolled in a relationship are called its participants

EXAMPLE-   Employees are assigned to projects

                    Projects have sub-tasks

                    Departments manage one or more projects

TYPES OF RELATIONS-

1.) 1:M(One to many)-In a one-to-many relationship, each row in the related to table can be related to many rows in the relating table. This allows frequently used information to be saved only once in a table and referenced many times in all other tables.

EXAMPLE-In class there is only one faculty member and there are number of children. This is an example of one to many relationship.

                                     (ONE-MANY RELATIONSHIP)

2.)M:M (Many to many relationship)-A many-to-many relationship refers to a relationship between tables in a database when a parent row in one table contains several child rows in the second table, and vice versa. Many-to-many relationships are often tricky to represent.

EXAMPLE- There are so many skills of a person and its vice versa.

                                      (MANY-MANY RELATIONSHIP)

 3.) M:1(Many to one relationship)- A many-to-one relationship is where one entity (typically a column or set of columns) contains values that refer to another entity (a column or set of columns) that has unique values. In relational databases, these many-to-one relationships are often enforced by foreign key/primary key relationships, and the relationships typically are between fact and dimension tables and between levels in a hierarchy.

EXAMPLE- In any company there are no of stores and for one store there should be one head employee.

4.) 1:1(One to one relationship)-In a one-to-one relationship, each row in a table is related to a single row in another table.

EXAMPLE- 

In a warehouse application a storage-bin table might have a one-to-one relationship with a widget table. This application would model a physical warehouse where each storage bin contains one type of widget and each widget resides in one storage bin.

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Network model and their Advantages and Disadvantages | Data models

NETWORK MODEL

INTRODUCTION-

The network model is a database model conceived as a flexible way of representing objects and their relationships. Its distinguishing feature is that the schema, viewed as a graph in which object types are nodes and relationship types are arcs, is not restricted to being a hierarchy or lattice.

The network model replaces the hierarchical model with a graph thus allowing more general connections among the nodes.The main difference of the network model from the hierarchical model is its ability to handle many to many relationships.In other words it allow a record to have more than one parent.

EXAMPLE-

ADVANTAGES OF NETWORK MODEL-

The major advantage of network model are-

1.) Conceptual simplicity-Just like the hierarchical model,the network model is also conceptually simple and easy to design.

2.) Capability to handle more relationship types-The network model can handle the one to many and many to many relationships which is real help in modeling the real life situations.

3.) Ease of data access-The data access is easier and flexible than the hierarchical model.

4.) Data integrity- The network model does not allow a member to exist without an owner.

5.) Data independence- The network model is better than the hierarchical model in isolating the programs from the complex physical storage details.

6.) Database standards

DIS-ADVANTAGE OF NETWORK MODEL-

1.) System complexity- All the records are maintained using pointers and hence the whole database structure becomes very complex.

2.) Operational Anomalies- The insertion,deletion and updating operations of any record require large number of pointers adjustments.

3.) Absence of structural independence-structural changes to the database is very difficult.

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Network model and its Advantages | data models

NETWORK MODEL

INTRODUCTION-

The network model is a database model conceived as a flexible way of representing objects and their relationships. Its distinguishing feature is that the schema, viewed as a graph in which object types are nodes and relationship types are arcs, is not restricted to being a hierarchy or lattice.

                The network model replaces the hierarchical model with a graph thus allowing more general connections among the nodes.The main difference of the network model from the hierarchical model is its ability to handle many to many relationships.In other words it allow a record to have more than one parent.

EXAMPLE-

ADVANTAGES OF NETWORK MODEL-

The major advantage of network model are-

1.) Conceptual simplicity-Just like the hierarchical model,the network model is also conceptually simple and easy to design.

2.) Capability to handle more relationship types-The network model can handle the one to many and many to many relationships which is real help in modeling the real life situations.

3.) Ease of data access-The data access is easier and flexible than the hierarchical model.

4.) Data integrity- The network model does not allow a member to exist without an owner.

5.) Data independence- The network model is better than the hierarchical model in isolating the programs from the complex physical storage details.

6.) Database standards

DIS-ADVANTAGE OF NETWORK MODEL-

1.) System complexity- All the records are maintained using pointers and hence the whole database structure becomes very complex.

2.) Operational Anomalies- The insertion,deletion and updating operations of any record require large number of pointers adjustments.

3.) Absence of structural independence-structural changes to the database is very difficult.

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Relational model | Data models

RELATIONAL MODEL

INTRODUCTION-

Relational model stores the data in the form of table. It consists of three major components.

1.) The set of relations and set of domains that defines the way data can be represented.

2.) Integrity rules that defines the procedure to protect the data.

3.) The operations that can be performed on the table.

CHARACTERISTICS-

Characteristics of relational database are:-

1.) All data is conceptually represented as an orderly arrangement of data into rows and column called a relation or table.

2.) All the values are scaler i.e. at any given row or column position there is one and only one value.

3.) All operations are performed on the entire relation and the result is an entire relation.

BASIC TERMINOLOGY OF RELATIONAL DATABASE-  

1.) TUPLE OF A RELATION-Each row in a table is known as tuple.

2.) CARDINALITY OF A RELATION-  It is the no of tuples in the relation.

3.) DEGREE OF A RELATION-No of columns is known as degree of a relation.

4.) DOMAIN OF A RELATION-It defines the kind of data represented by the attribute.It is the set of all possible values that an attribute may contain.

5.) BODY OF THE RELATION-It consists of an unordered set of 0 or more tuples.

EXAMPLE:- Consider a table

1.) TUPLE OF A RELATION-  8

2.) CARDINALITY OF A RELATION-  8

3.) DEGREE OF A RELATION- 5

4.) DOMAIN OF A RELATION- All the data entered in the table is the domain of a relation.

KEYS OF A RELATION-

1.) PRIMARY KEY- It is the key that uniquely identifies a record. It doesn't have null values.

2.) FOREIGN KEY- It refers to the primary key of some other table.It permits only those values which appear in the primary key of the table to which it refers.

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Hierarchical model (Record based data model) | Data models

HIERARCHICAL MODEL(RECORD BASED DATA MODEL)

INTRODUCTION-

It is developed to manage large amounts of data for complex manufacturing projects.

                             (STRUCTURE OF HIERARCHICAL MODEL)

This structure contains levels or segments.The top layer is known as the parent of the segment .Root segment is the parent of level 1 segment.This model defects a set of one to many relationship between parent and children segments.E.G COLLEGE STRUCTURE

ADVANTAGES OF HIERARCHICAL MODEL:-

1.) It provides simplicity and it is easy to design.

2.) It also provide data integrity.Since, it is based on parent-child relationship.So, there is always a link between these segments.

DRAWBACKS OF HIERARCHICAL MODEL:-

1.) There exist operational anomalies in this model.

2.) Implementation Complexity

3.) It is easy to design but very difficult to implement.

4.) Database Management System-If you make any change in the database structure then you need to make all the necessary changes in all the application program that access the database.

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Data models and their types | database managenent system

DATA MODELS

INTRODUCTION:-
It can be  defined as an integrated collection of concepts for describing and manipulating data,relationship between data and the constrains of the data in any organization.

It consists of three components:-

1.)Structured part:- It consist of set of rules according to which database can be connected.

2.) Manipulative part:- It defines the types of operations that are allowed on data.

3.) Set of integrity rules:-It ensures that the data is accurate.

PURPOSE OF DATA MODEL:- Purpose of data model is to represent the data and to make it understandable.

TYPES OF DATA MODEL:-

There are 3 types of data models:-

1.) Object based data models

2.) Physical data models

3.) Record based

1.) OBJECT BASED DATA MODELS:-It uses the concepts such as entities,attributes and relationship.It is of further 4 types:-

1.) ER(entity relationship)model

2.) Object oriented ER model

3.) Semantic model

4.) Functional model

2.) PHYSICAL DATA MODEL:-It describes how the data is stored in the computer representing the information such as record structure ,record modeling and access paths.

3.) RECORD BASED DATA MODEL:- These are used in describing the data at logical and view levels.These are used to specify the overall logical structure of the database.Record database models are of 3 types which are:-

1.) Hierarchical model

2.) Network model

3.) Relational model

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