Chapter 1 Introduction. February 2008Database System Concepts- Chapter1 Introduction -2 Main Parts...

Chapter 1

Introduction

February 2008 Database System Concepts- Chapter1 Introduction - 2

Main Parts in This Chapter

Database System Applications Purpose of Database Systems View of Data Database Languages Relational Database Database Design Data Storage and Querying Transaction Management Database Architectures Database Users and Administrators History of Database Systems Appendix: Data, Information, Knowledge, etc.


§1.0 DB, DBMS, DBS

Definitions in the textbook Database (DB)

— a collection of interrelated data, stored in systems as files Database management system (DBMS)

— DB, or a collection of interrelated data

— set of programs to access the data in DB Database system (DBS)

having the same definition as DBMS in the textbook the term DBS and DBMS are used interchangeably in the

textbook


§1.0 DB, DBMS, DBS(cont.)

DBMS provides an environment that is both convenient and efficient for store and retrieve information definition of structures for storage of information data manipulation mechanisms data safety mechanisms

Definitions in some other textbooks Fig. 1.0.1 Database(DB)

— a collection of interrelated data , stored in systems as files


§1.0 DB, DBMS, DBS(cont.)

Definitions in some other textbooks (cont.) Database management system (DBMS)

— a system/mechanism to manage data in DB

— or: set of programs to access the data in DB Database system(DBS)

— DB + DBMS + Users/Administers Database application system

— DB + DBMS + Application programs + Users/Administers

DBMS

Application program 1 DB file

…

DB query language e.g. SQL

API, e.g.ODBC, JDBC

Users DBMS DB

DBS/DBAS

Fig.1.0.1 DBS and DBAS

Application program 1


Databases and DBS touch all aspects of our lives 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

§1.2 Purpose of Database Systems


In the early days, database applications were built on top of file systems

E.g. Saving-bank enterprise a number of application programs to access data files

A program to debit （将 .. 记入借方） or credit （将 .. 记入贷方） an account( 帐户）

A program to add a new account A program to find the balance （收付差额，余额） of

an account A program to generate monthly statements

§1.2 Purpose of Database Systems (cont.)


Data management on the basis of file systems Example— customer_record=<c_name, c_id, street, city> in

Customer_File FS access need — file name, item name, length of record, length of item ,

position of item in the record, storage structure, access method, ….

Demerit— application programs are not independent of the file system

( or operating system)— dependency among application programs and data ( 程序与

数据的非独立 / 依存性）


Fig. 1.0.2 Why DBS needed

secondary storage (e.g. disk, tape)and data on it (address: cylinder, track, sector)

memory controllers (i.e. disk controller), on the basis of secondary storage’s physical structures,

such as storage structures, access method

access programs

(I)

direct accessthrough

disk controller

(I)

access through OS’ file system (II)

access through data base system

(DBS)(III)

access programs

(II)

access programs

(III)

I/O system : drivers

file system:file’s logical structures and access methods

DBMS: relational tables’ logical structures and access methods

system calls related to file management

DBS API

Select *From Student Where S#=100

DBSlogicalstructures:

relations/tuples

DBMSDB user

Logical address: #Record

Record1

Record k

…

block1

OS: Logical file

…Record i

Record m

…Block n

Physical address：platter/track/sector

block1

Block i

Block k

……

Physical File on disk

DB files

block

OS： file system and I/O subsystem

view of data model

view of file

Fig. 1.0.3 Database access


Drawbacks of using file systems to store data data redundancy （冗余） and inconsistency （不一致性）

multiple file formats, duplication （副本） of information in different files

difficulty in accessing data need to write a new program to carry out each new task

data isolation （独立性） multiple files and formats



integrity （完整性） problems data values should satisfy consistency constraints integrity constraints (e.g. account balance > 0) become

part of program code hard to add new constraints or change existing ones

atomicity problems 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 anomalies 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

§1.2 Purpose of Database Systems(cont.)


§1.3 View of Data

Basic concepts in DBS theory view of data (数据视图 ), data abstract data model, data schema ( 模式 ), schema instance logical /physical isolation

1.3.1 Data abstraction To simplify and “divide and conquer” the design of complex

data application systems describes/design application data in three levels, and

obtains three types of schema Fig. 1.1

Fig.1.1 The three levels of data abstraction


View level describes data from different view of data

in application areas, data item and associations among them

several views for one datum description results

external schema ( 外模式） ={view}, set of views description procedure/Logical DB design

view abstraction merits: application programs are programmed according

to views, hiding details of data types. Views can also hide information (e.g., salary) for security purposes.

1.3.1 Data abstraction (cont.)


E.g. Banking Application Areas in Fig. 6.25 in page 240 in view-level, finding objects, object’s features, and

associations among objects from more than one viewpoints, view integration view1: customer<id, name, street, city> view2: loan<loan-number, amount> view3: account<account-number, balance> view4: customer <borrower, loan> view5: customer <depositor, account> view6: …. ……. be represented as relational views



Logical level implementation-oriented, describes how data are stored in

DBS as relational tables:

table customer name : string;street : string;city : integer;

description results logical schema ( 逻辑模式） , e.g. relational tables

description procedure/Logical DB design logical abstraction

Merits: hiding physical implementation details



Physical level describes how the data (e.g., customer record/table) are

actually stored in files ( or in secondary storage) description results

physical/internal schema ( 物理模式，内模式） i.e. storage structure and access methods, such as index,

physical blocks, access methods for secondary memory, etc.

description procedure/Physical DB design physical abstraction



An instance of the database the collection of information stored in the database at a

particular moment (P7 in the textbook) the actual content of the database at a particular point in

time Schema

the structure of the database overall design of the database??? (P7 in the textbook) physical schema

database design at the physical level logical schema

database design at the logical level

1.3.2 Instances and Schemas


Data model , data schema (of data model), instance of schema

E.g. relational data model : R={ <a1, a2, …., an> } relational data schema : customer=<c_name, c_id, street,

city> instance of schema : <Wang_Li, 1001, Haidian, Beijing

> similar to data types declaration, variables of data types,

and values of variables e.g. Fig.1.2

1.3.2 Instances and Schemas (cont.)


Data descriptions/abstractions in three levels must obey three types of specification, i.e. three types of data models

Definition of data model (P8) a collection of conceptual tools for describing

data data relationships data semantics data constraints

程序 = 数据结构 + 算法

integrity constraints

1.3.3 Data Model


Another definition of data model DBS 中对数据组织与管理 / 使用方式的抽象描述，包括

数据组织的语法定义，如数据项、数据项间的联系数据组织的语义定义，如完整性约束数据操作 (note: only in some data models, e.g.

relational data model) Relational model ( 关系模型 )

using a collection of tables to represent both data and the relationships among those data

a set of operations on tables are also defined (§2.2/ 2.3/2.4) e.g. Fig.1.4

1.3.3 Data Model (cont.)


Entity-Relationship model ( 实体 - 联系模型 ) using the entity and the relationship to model the object and

the association among objects e.g. Fig.1.3

Network model and hierarchical model only used for early DBS

Other models object-oriented model (Chapter 9) semi-structured data models (Chapter 10)



Data models can be classified as object-based model ( 基于对象的模型 ) record-based model ( 基于记录的模型 ) physical data model ( 物理数据模型 )

For more details about category of data models, refer to Appendix B



3 种数据抽象、 3 种模式→ DBS中 2 种数据独立性概念 / 逻辑模式→内模式间的映射与 physical data

independence 外模式→概念模式间的映射与 logical data independence refer to Fig.1.0.4

1.3.4 Data Independence

Logical data independence when DBS’s logical schemas at logical level (DBMS-

oriented) change, application-oriented external schema or application programs do not change

e.g. customer=<c_name, c_id, street, city> is extended into customer=<c_name, c_id, street, city, c_age, c_sex>

用户 A1

宿主语言+ DML

用户 A2 用户 B1 用户 B2

外部视图 A 外部视图 B

概念 / 逻辑视图

外模式

概念 / 逻辑模式

内模式

DBMS

外模式 / 概念模式映射 A

外模式 / 概念模式映射 B

概念模式 / 内模式映射

宿主语言+ DML

宿主语言+ DML

宿主语言+ DML

Fig. 1.0.4


Physical data independence (P7) application programs do not depend on DBS’s physical

schema, i.e. when physical schema (e.g. index, block-size) change, application programs remain unchanged

the ability to modify the physical schema without changing the external/logical schemas, on which application programs depend

1.3.4 Data Independence (cont.)


§1.4 Database Language

Database Languages as human-machine interfaces data manipulation language, DML data definition language, DDL

1.4.1 Data manipulation language DML is the language that enables users to access or manipulate

the data as organized by the appropriate data model

Types of DBS access retrieve , insert, delete, modify


Two types of DML procedural ( 过程性 ) – user specifies what data is required

and how to get those data nonprocedural ( 说明性， declarative) – user specifies what

data is required without specifying how to get those data Query( 查询）

a statement requesting the retrieval of information DML also known as query language

1.4.1 Database Manipulation Language (cont.)


SQL is the most widely used non-procedural query language, others are QE, Datalog

Example find the name of the customer with customer-id 192-83-7465

select customer.customer-namefrom customerwhere customer.customer-id = ‘192-83-7465’

1.4.1 Database Manipulation Language (cont.)


DDL is used for specifying the database schema and additional properties of the data

E.g. create table account ( account-number char(10), balance integer)

DDL can also be used to define integrity constraints in DB domain integrity, referential integrity, assertions,

authorization, etc. The structures /schemas of the database defined by DDL is stored

in the data dictionary/directory meta data, i.e., data about data, is stored

1.4.2 Database Definition Language


Data storage and definition language a subset of DDL, defining physical schemas, i.e., storage

structure and access methods, which are usually hidden form users

1.4.2 Database Definition Language (cont.)


Application programs generally access databases in two methods application program interfaces (API, e.g. ODBC/JDBC)

which allow SQL queries to be sent to a database Fig. 1.0.5

embed DML call within host language ( 宿主语言 , such as C and Java)

1.4.3 DB Access for Application Programs


C applicationprograms

Java applicationprograms

Other language application

programs

ODBC JDBC

DBS

DDL+ DML

API

Fig.1.0.5 DBS access interfaces

1.4.3 DB Access for Application Programs(cont.)


§1.5 Relational Database

Refer to chapter 2


§1.6 Database Design

1.6.1 Design process 从保持 data independence （数据无关性 / 独立性）角度出发，

根据 data models 所定义的数据规范形式，在 view、 logical 、 physical 三个层次，采用三种 data abstraction 方法，通

过 DB 概念设计、 DBS 逻辑设计、 DBS 物理设计三个阶段，构造面向具体应用领域的 DBS 的 external schema、 logical schema 、 internal schema 的集合 , 从而得到 conceptual DBS 、 logical DBS 、 physical DBS 的设计结果

As described in Fig.1.0.6 conceptual design logical design physical design

逻辑模式LS, 外模式

Entity-Relationship model

Logical Schema LSi.e. Relational Model，Hierarchical/Network Model

Internal Schema ISi.e. Unifying Model or Frame Memory Model

现实世界(应用领域）

物理抽象

视图抽象

逻辑抽象

DBS逻辑设计与逻辑DBS

DBS概念设计与概念DBS

DBS物理设计与物理DBS

视图1

视图n

DBS设计与设计阶段：数据模型—数据抽象—数据模式

视图2

内模式IS

Fig. 1.0.6 Data abstraction and Schema


Banking Enterprise the bank is organized into branches each branch is described by the city is located in, the name

and the assets a bank customer is illustrated by his customer_id and name,

the street and city the bank offers two types of accounts, which are depicted by

account_number and balance

— the savings account: an interest rate

— the checking account: overdraft

1.6.2-1.6.4 An Example


the bank provides its customers with loans, which are depicted by loan_number, balance_name, and amount

Bank employees are identified by their employee_id, telephone_number, employee_ street, employee_ city

Conceptual DB design E-R diagram e.g. Fig.1.3

1.6.2-1.6.4 An Example (cont.)


Fig.1.3 A sample entity-relationship model



Logical DB design database design in E-R model usually converted to design in

the relational model, i.e the relational tables and views the converted relational tables are then normalized ( 规范

化 ) e.g. Fig.1.4 and Fig.1.5



Attributes

(a) The customer table

Fig.1.4 A Sample Relational Database

schema

instances



Fig.1.4 A Sample Relational Database



Fig 1.6 DBS = User/DBA + DBMS + DB DBMS

query processing storage manager

DB files application data data dictionary/directory indices statistic data

§1.11 DBS Architecture

Fig. 1.6DBS Architecture

user

DBMS

DB


DBAS DB + DBMS + Application programs + Users/DBA 实现数据处理功能

DBS DB + DBMS + User/DBA 实现数据管理功能

信息 / 数据管理（ management）数据的分类、收集、组织、编码、存储、检索和维护

信息 / 数据处理（ processing）对数据进行分类、收集、组织、存储，进而从已有数据出

发，抽取或推导出新的数据 / 信息

1.11 Database Application System


信息 / 数据处理与信息 / 数据管理的区别数据管理侧重于对数据如何进行组织和存储，并根据用

户需要提供对数据的访问支持数据处理除了具有数据管理功能外，还可以对通过数据

管理得到的数据进行进一步深加工，从中获取新的数据、信息

例如，在一个商品零售系统中，可以利用数据库系统的数据管理功能存储各种商品基本信息（如商品数量、销售额等）并为各类用户提供对各类商品信息的查询功能。当从数据库系统中得到这些商品信息后，可以采用一些统计分析工具、数据挖掘（ Data Mining ）工具进一步进行分析处理，得到有关那些商品属于热销商品、热销商品销售销售额等新信息。这种统计分析属于数据处理范畴

1.11 Database Application System(cont.)


1.11 Database Application System Architecture

Fig.1.7 In DBAS, the application programs are responsible for

information or data processing, e.g. data mining

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”

February 2008 Database System Concepts- Chapter1 Introduction - 51Fig.1.7 Two-tier and three-tier architectures

1.11 Database Application System Architecture (cont.)


In DBS, DBMS provides data management mechanisms for users, that is data storage and data querying

DBMS consists of two modules storage manager query processor

Storage manager is a program module that provides the interface between the low-level data stored in the database and the application programs and queries submitted to the system

The storage manager is responsible for translating DML statements into low-level file commands efficient storing, retrieving and updating of data

§1.8 Data Storage and Querying


The modules in the storage manager are authorization and integrity manager, transaction manager,

file manager, and buffer manager

The query processor includes DDL interpreter DML compiler Query optimization Query evaluation engine

1.8 Data Storage and Querying (cont.)

C, Pascal programs

词法 / 语法 / 语义分析

中间代码生成

( 中间 ) 代码优化

目标代码生成

程

序

编

译 /

编译器

程序执

行 /

OS

进程管

理

&

进程调

度并发控制

死锁处

理

SQL query

扫描和语法 / 语义分析

查询优化( 优化后 ) 查询执行计划

查询代码生成

查询处理 / D

BM

S

process / thread事务、存储处理 /

DB

MS

Chapter13, 14

Chapter15,16, 17

transaction

关系代数表达式 & 查询树

查询计划执行的代码

事务管

理

目标程序代码

(§14)&

事务调

度并发控制

死锁处

理恢复技

术

(§13)

(§15) (§16) (§17)


A transaction is a collection of operations that performs a single logical function in a database application

E.g. Transaction T1: transfer $50 from account_A to account_B T1 : read ( account_A );

account_A := account_A -50; write (account_A ); read (account_ B ); account_ B := account_ B + 50; write (account_ B );

integrity constraint total amount of account_A and account_B remains unchanged before and after the transaction execution

§1.9 Transaction Management


Transaction properties atomicity (原子性 ), consistency ( 一致性 ), isolation ( 独

立性 ), durability( 持久性 ) Transaction-management component in DBMS

ensures that the database remains in a consistent/correct state despite system failures (e.g., power failures and operating system crashes) and transaction failures, by means of concurrency and control failure recovery.

controls the interaction among the concurrent transactions, to ensure the consistency of the database

1.9 Transaction Management


§1.12 Database User and Administrators

1.12.1 Database users and user interfaces Users are differentiated by the way they expect to interact with the

system, four categories of users, four categories of interfaces: Fig.1.6

naive users – invoke one of the permanent application programs that have been written previously

e.g. people accessing database over the web, bank tellers, clerical staff

application programmers – interact with system through DML calls

sophisticated users – form requests in a database query language or tools, and submit these queries to the query processor


specialized users – write specialized database applications that do not fit into the traditional data processing framework,

1.12.2 Database Administrator (DBA) The responsibilities of DBA include

schema definition schema and physical organization modification granting of authorization for data access routine maintenance

§1.12 Database User and Administrators (cont.)


Appendix A Data, Information, Knowledge

1.0.1 Definitions in Microsoft Press Computer Dictionary data

Plural of datum , an item of information Information:

the meaning of the data as it is intended to be interpret by people. Data consist of facts, which become information as they are seen in context and convey meaning to people. Computer process data without any understanding of what the data represents


Appendix A Data, Information, Knowledge (cont.)

1.0.2 Definitions in Longman Dictionary of Contemporary English

data facts, information information in a form that can be processed and stored in

computers Information

knowledge in the form of facts and news


knowledge what a person knows; the facts, information, skills and understanding that one

has gained, esp. through learning or experience

1.0.3 Definitions in Cambridge International Dictionary of English

Data information, esp. facts or numbers , collected for

examination and used to help decision—making or, information in a electronic form that can be processed

by computers



Information knowledge about something , esp. facts and news

Knowledge information, esp. facts or numbers , collected for

examination and used to help decision—making understanding of ,or information about a subject which has

been obtained by experience or study, and which is either in a person’s mind or possessed by people generally



Appendix AInformation Theory (cont.)

什么是信息？是一种人人皆知的抽象概念，无确切定义，具有两个

明显的特征：广泛性与抽象性。

广泛性可从以下三方面来理解客观世界充满着信息：

— 一切客观物质无不具有自己的特征信息。人类离不开信息— 人的五官在不停地感知、接收信息；人的神经系统在

不停地传递信息；人的大脑则在不停地处理与决策信息；人与人之间又在不停地交流信息；人活在世上百分之百时间都在自觉与不自觉地与信息打交道。



知识、书本是有用信息的积累

抽象性则是指信息是组成客观世界并促进社会发展的三大基本要素之一

三大要素是：物质、能量与信息物质是基础，是实体。能量是物质运动的形式， E=mc2 ，物质可转换成能量，

而能量又是改造客观世界的主要动力。



信息：它依附于物质和能量，但又不同于物质和能量。没有信息就不能更好地利用物质和能量，人类利用信息和知识改造物质，创造新物质，提高能量利用效率，发现新能量形式。信息也是客观存在的，它是人类认识、改造客观世界的主要动力，是人类认识客观世界的更高层次。

在通信中对信息的表达分为三个层次：信号、消息、信息信号：是信息的物理表达层，是三个层次中最具体的

层次。它是一个物理量，是一个载荷信息的实体，可测量、可描述、可显示。



消息： (或称为符号 ) 是信息的数学表达层，它虽不是一个物理量，但是可以定量地加以描述，它是具体物理信号的进一步数学抽象，可将具体物理信号抽象为两大类型：离散 (数字 ) 消息 , 连续 (模拟 ) 消息，

信息：更高层次哲学上的抽象，是信号与消息的更高表达层次。

三个层次中，信号最具体，信息最抽象。它们三者之间的关系是哲学上的内涵与外延的关系

信息可以认为是具体的物理信号、数学描述的消息的内涵，即信号具体载荷的内容、消息描述的含义



信号是抽象信息在物理层表达的外延消息是抽象信息在数学层表达的外延

同一信息，可以采用不同的信号形式 ( 比如文字、语言、图象等 ) 来载荷；同一信息，也可以采用不同的数学表达形式 ( 比如离散或连续 ) 来定量描述。同样，同一信号形式，比如“ 0” 与“ 1” 可以表达不同形式的信息，比如无与有、断与通、低与高 ( 电平 )等等。


Data models can be classified as object-based data model( 基于对象的数据模型 ) record-based data model( 基于记录的数据模型 ) physical data model( 物理数据模型 )

基于对象（ Object-based ）的数据模型用处： DBS 概念设计阶段，在概念和视图级别上描述

数据，定义 DBS 概念 / 外模式，生成概念 DBS 包括：实体—联系模型、面向对象（ object-oriented ）

数据模型面向对象模型 : 对象、对象类 ; 类 = 变量 / 属性

+ 方法

Appendix B Category of Data Model


基于记录的数据模型用处： DBS 逻辑设计阶段，生成数据库逻辑模式。与

DBMS相关，决定了不同的 DBS 类型。包括：关系数据模型、层次型数据模型、网状数据模型

物理数据模型用处： DBS 物理设计阶段，定义 DBS的 DBS文件的物

理存储结构和存取方法，生成物理数据库模式。与DBMS和 DBS 的实现相关。

包括： Unifying Model、 Frame Memory Model

Appendix B Category of Data Model (cont.)


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