1. Faculty of Computer and Information Communication
Solution-based
Database System Concepts 4th ED
Chapter 1. Introduction
Faculty of Computer and Information Communication
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2. Solution-based Course
This lecture is run with some solution-based subjects adapted to each chapter.
The solution includes some topics needed in real business applications.
Through this lecture, students can get an indirect experience.
The courseware writing is supported by NURI of ministry of education.
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Contents
Purpose of Database Systems
View of Data
Data Models
Data Definition Language
Data Manipulation Language
Transaction Management
Storage Management
Database Administrator
Database Users
Overall System Structure
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4. Database Management System (DBMS)
Collection of interrelated data + a set of programs to access them
Database contains information relevant to an enterprise
The primary goal of a DBMS is to provide a way to store and retrieve database information that is both convenient and efficient.
Database system are designed to manage large bodies of information. Management of data involves both:
defining structures for storage of information
providing mechanisms for the manipulation of information
ensuring the safety despite system crashes or attempts at unauthorized access.
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DBMS (cont.)
Database Applications:
Banking: Customer Information, accounts, loans, banking trans.
Airlines: reservations, schedule information in a geographically distributed manner
Universities: student information, course registration, grades
Credit and transaction, Telecommunication, Finance
Sales: customers, products, purchases
Manufacturing: production, inventory, orders, supply chain
Human resources: employee records, salaries, tax deductions
Databases touch all aspects of our lives
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6. Purpose of Database System
Major drawbacks of file processing system:
Data redundancy and inconsistency
Multiple file formats, duplication of information in different files
Difficulty in accessing data
Need to write a new program to carry out each new task
Data isolation
multiple files and different formats
Integrity problems
Integrity constraints (e.g. account balance > 0) become part of program code
Hard to add new constraints or change existing ones
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7. Purpose of Database Systems (Cont.)
Drawbacks of using file systems (cont.)
Atomicity of updates
Failures may leave database in an inconsistent state with partial updates carried out
E.g. transfer of funds from one account to another should either complete or not happen at all
Concurrent access by multiple users
Concurrent accessed needed for performance
Uncontrolled concurrent accesses can lead to inconsistencies
E.g. two people reading a balance and updating it at the same time
Security problems
Database systems offer solutions to all the above problems
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Levels of Abstraction
Physical level describes how a record (e.g., customer) is stored.
Logical level: describes data stored in database, and the relationships among the data.
Record type of Pascal-like high-level language:
type customer = record name : string; street : string; city : integer; end;
View level: application programs hide details of data types. Views can also hide information (e.g., salary) for security purposes.
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Data hierarchy?
Physical unit
bit < nibble < byte
Logical Unit
field < record < file < DB
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10. View of Data An architecture for a database system 2019-05-01
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Instances and Schemas
Similar to types and variables in programming languages
Databases change over time as information is inserted and deleted
Schema – the logical structure of the database
e.g., the database consists of information about a set of customers and accounts and the relationship between them)
Analogous to type information of a variable in a program
Physical schema: database design at the physical level
Logical schema: database design at the logical level
Instance – the actual content of the database at a particular moment: Analogous to the value of a variable
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12. Instances and Schemas (cont.)
Physical Data Independence – the ability to modify the physical schema without changing the logical schema
Applications depend on 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.
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Data Models
Underlying the structure of a database
A collection of tools for describing
data
data relationships,data semantics,data constraints
Entity-Relationship model
a perception of a real world: a collection of basic objects, entities and relationship among them
Relational model
a collection of tables to represent both data and the relationships among the data
Other models:
object-oriented model,semi-structured data models( XML ), network model and hierarchical model
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14. Entity-Relationship Model
-Example of schema in the entity-relationship model
Rectangles, which represent entity sets
Ellipses, which represents attributes
Diamonds, which represent relationship among entity sets
Lines, which link attributes to entity sets and entity sets to relationship
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15. Entity Relationship Model (Cont.)
E-R model of real world
Entities (objects)
E.g. customers, accounts, bank branch
Relationships between entities
E.g. Account A-101 is held by customer Johnson
Relationship set depositor associates customers with accounts
Widely used for database design
Database design in E-R model usually converted to design in the relational model (coming up next) which is used for storage and processing
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Relational Model
Example of tabular data in the relational model.
Attributes
customer-
name
customer-
street
customer-
city
account-
number
Customer-id
Johnson
Smith
Jones
Alma
North
Main
Palo Alto
Rye
Harrison
A-101
A-215
A-201
A-217
-each table has multiple columns, which has a unique name.
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17. A Sample Relational Database
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Data Language
DDL(data definition language)
Specification notation for defining the database schema
create table account ( account-number char(10), balance integer)
DDL compiler generates a set of tables stored in a data dictionary
Data dictionary contains metadata
Data about data. database schema
Data storage and definition language
language in which the storage structure and access methods used by the database system are specified
Usually an extension of the data definition language
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19. Data Manipulation Language (DML)
Language for accessing and manipulating the data organized by the appropriate data model
DML also known as query language
Two classes of languages
Procedural – user specifies what data is required and how to get those data
Nonprocedural – user specifies what data is required without specifying how to get those data
SQL is the most widely used nonprocedural query language
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20. SQL(Structure Query Language)
SQL: widely used non-procedural language
E.g. find the name of the customer with customer-id select customer.customer-name from customer where customer.customer-id = ‘ ’
E.g. find the balances of all accounts held by the customer with customer-id select account.balance from depositor, account where depositor.customer-id = ‘ ’ and depositor.account-number = account.account-number
Application programs generally access databases through one of
Language extensions to allow embedded SQL
Application program interface (e.g. ODBC/JDBC) which allow SQL queries to be sent to a database
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Database Users
Users are differentiated by the way they expect to interact with the system
Naive users – invoke one of the permanent application programs that have been written previously
E.g. bank tellers involve a program called transfer.
Application programmers – interact with system through DML calls
Sophisticated users – interact with the system without writing programs and form requests in a database query language
Specialized users – write specialized database applications that do not fit into the traditional data processing framework eg) CAD, KB, expert systems
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22. Database Administrator
Coordinates all the activities of the database system; the database administrator has a good understanding of the enterprise’s information resources and needs.
Database administrator's duties include:
Schema definition
Storage structure and access method definition
Schema and physical organization modification
Granting user authority to access the database
Specifying integrity constraints
Acting as liaison with users
Monitoring performance and responding to changes in requirements
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23. Transaction Management
A transaction is a collection of operations that performs a single logical function in a database application
Transaction-management component ensures that the database remains in a consistent (correct) state despite system failures (e.g., power failures and operating system crashes) and transaction failures.
“all or none” or “all or nothing”
Concurrency-control manager controls the interaction among the concurrent transactions, to ensure the consistency of the database.
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24. Database System Structure
Storage Manager is a program module that provides the interface between the low-level data stored in the database and the application program and queries.
interaction with the file manager
efficient storing, retrieving and updating of data
components:
Authorization and integrity manager
Transaction manager
File manager
Buffer manager
Physical System Implementation:
Data files, Data dictionary, Indices
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25. Database System Structure (cont.)
The Query Processor
DDL interpreter
DML compiler
Query evaluation engine
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26. Application Architecture
Two-tier architecture
client
database sever
Three-tier architecture
application server
database server
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27. Overall System Structure
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28. Application Architectures
Two-tier architecture: E.g. client programs using ODBC/JDBC to communicate with a database
Three-tier architecture: E.g. web-based applications, and applications built using “middleware”
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29. Silberschartz-Korth-Byun
데이터베이스 시스템의 역사
1950년대와 1960년대 초반
천공카드 입력, 자기테이프 저장, 월급지급 자동화 => 순차파일 방식 처리
1960년대 후반 ~ 1970년대
하드디스크로 획기적 자료처리, 자료구조 기반 네트워크 또는 계층 DB 등장
1970 Codd 관계형 모델 정의, 비절차적 질의 방식 제안, RDBS 탄생, Codd 튜링상 수상
1980년대
시스템 성능 저조, IBM의 시스템 R에 의한 상황변화로 SQL/DS 탄생, 이후 IBM DB2, Oracle, Ingres, DEC Rdb이 효율적 질의 처리 기법 발전
80년대 초반, 관계형 모델이 계층모델이나 네트웤 모델의 성능 추월 경쟁력 갖춤
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30. Silberschartz-Korth-Byun
데이터베이스 시스템의 역사(계속)
1980년대(계속)
선언적 질의 작성으로 사용하기 매우 쉽다.
1980대 이후 관계형 모델은 제왕적 위치
또한 이 시기에 병렬,분산 데이터베이스 연구 활발, 객체지형 데이터베이스 태동
1990년대 초반
트랜잭션 처리 중심에서 의사결정 시스템과 질의 처리가 주요 응용으로 부상, 대량의 자료 분석 도구 발달
1990년대 후반
웹의 발전으로 db의 초고속처리, 매우 견고한 신뢰성 확보
24 X 7 가용성 갖춤
웹 인터페이스 갖춤
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