01. Introduction to Database

Why use Database System

What is DBMS?

• Database(collection of data) Management system
• A collection of interrelated data and a set of programs to access those data

Drawback of file systems

• Data redundancy:
  • e.g. Student A address data is used in data B and C
• Data Inconsistency: e.g. If student A’s data has been modified, All data that contains student A, also have to be changed
• Difficulty in accessing data:
  • e.g. In DBMS we use unified query called sql, whereas needing separate program for file system
• Data isolation:
  • e.g. .txt file and .png file is scattered in file system, caused by different file format
• Integrity problems:
  • e.g. Students age should not be below zero
• Atomicity problems:
  • e.g. think about @Transactional annotation in SpringDataJPA
• Concurrent-access anomalies
  • e.g. a data is accessed concurrently
• Security problems

Data Models

Definitions – Collection of conceptual tools for Data, Data relationships, Data semantics, Consistency constraints

• Provides a way to describe the design og a database at yhe physical, logical, and view levels.

  e.g.

  • Relation Model
  • Entity-Relationship Model
  • Object Based Data Model
  • Semistructed Data Model (e.g. XML)

Why use models?

Useful when examining or managing parts of the real world

e.g.

• Airplane simulator
• Nuclear power plant simulator

As can see on examples using a model is often much cheaper and safer

Types of data models

• Relation Model (Entity-Relationship data model)
• Object-based data models
• Semi-structured data model(XML)

View of Data

A major purpose of a database system is to provide users with an abstract view of the data. Database system hides certain details of how the data is stored and maintained

Data Abstraction

• Database systems must retrieve data efficiently, making database system developers to use complex data structures.
• Since many users are not computer trained it’s important to show abstract view

Physical level(Lowest level of abstraction)

• How data is actually stored, describes complex low-level data structure in detail
• e.g. Index structures (B+-tree, Hash table,…), Slotted page

Logical Level

Type instructor = record 
                  ID: char(5);
                  name: char(20);
                  dept_name: char(20);
                  salary: numeric(8, 2);
                  end;

• What data are stored in the database, and what relationships exist among those data.
  • e.g. Database administrators, who must decide what information to keep in the database, use the logical level of abstraction.
  • usually programmers work at this level of abstraction.

    Physical Data Independence

    • The user of the logical level does not need to be aware of Insane complexity of physical level structures
    • Ability to modify the physical schema without changing the logical schema
    • In general, the interfaces between the various levels and components should be well-defined so that changes in some parts do not seriously influence others.

View Level(Highest abstraction level, a.k.a subschemas)

• Describes only part of the entire database.
• Exists to simplify their interation with the system.
• The system may provide many views for the same database.
• Hide details of logical level and provide a security mechanism
  • e.g. student support team cannot see the instructor’s salary.

Schemas and Instances

Schema

• The overall design of the database
• Analogous to the type of variable
• Logical Schema: the overall logical structure(design) of the database
  • Programmers construct applications by using the logical schema
  • The physical schema is hidden beneath the logical schema, and can usually be changed easily without affecting application programs(physical data independence)
• Physical Schema: the overall physical structure(design) of the database

Instance

• the actual content of the database at a particular time
• Analogous to the value of a variable