数据库系统概念第四版英文原版详解

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"数据库系统概念英文版4E" 《数据库系统概念》是数据库领域的经典之作，由Silberschatz、Korth和Sudarshan三位作者合著，第四版提供了高清的英文版本，适合读者深入学习和研究。这本书涵盖了一系列关于数据库系统的核心概念，包括数据模型、关系型数据库、面向对象数据库、XML、数据存储与查询以及事务管理等多个方面。 1. 数据模型（Data Models）数据模型是数据库系统的基础，书中介绍了三种主要的数据模型：实体-关系模型（Entity-Relationship Model）、关系模型（Relational Model）和面向对象模型（Object-Oriented Model）。实体-关系模型强调了实体之间的关系，关系模型则以表格形式表示数据，并通过SQL语言进行操作。 2. 关系型数据库（Relational Databases）关系型数据库是目前最广泛使用的数据库类型，该部分详细讲解了SQL语言（Structured Query Language），它是用于管理关系数据库的标准语言，还涵盖了其他关系语言和关系数据库设计。此外，还讨论了数据完整性和安全性问题，确保数据库的可靠性和保护数据免受恶意攻击。 3. 面向对象数据库和XML（Object-Based Databases and XML）随着软件技术的发展，面向对象数据库（Object-Oriented Databases）和XML（eXtensible Markup Language）逐渐受到关注。面向对象数据库将对象的概念融入数据库，提供了更符合程序员思维的数据存储方式。XML则是一种用于标记数据的开放标准，常用于数据交换和存储半结构化数据。 4. 数据存储与查询（Data Storage and Querying）这部分涉及数据库的内部存储结构，如文件结构、索引（Indexing）和哈希（Hashing）。同时，详细阐述了查询处理（Query Processing）和查询优化（Query Optimization）的重要性，这些都是提高数据库性能的关键因素。 5. 事务管理（Transaction Management）事务是数据库操作的基本单位，保证了数据的一致性。书中详细讲解了事务的特性（ACID属性：原子性、一致性、隔离性和持久性）、并发控制（Concurrency Control）以及恢复系统（Recovery System），确保在多用户环境下数据的正确性和可靠性。 6. 数据库系统架构（Database System Architecture）最后，作者探讨了数据库系统的架构，包括单用户和多用户环境下的数据库设计，以及分布式数据库和并行数据库的概念，这有助于理解数据库如何在各种环境中高效运行。本书内容全面，适合计算机科学专业的学生、数据库研究人员以及需要深入了解数据库原理和实践的专业人士阅读。通过学习，读者能够掌握数据库系统的核心概念和技术，为实际工作中的数据库设计和管理提供坚实的理论基础。

Silberschatz−Korth−Sudarshan:

Database System

Concepts, Fourth Edition

1. Introduction Text

Companies, 2001

2 Chapter 1 Introduction

• Credit card transactions: For purchases on credit cards and generation of month-

ly statements.

• Telecommunication: For keeping records of calls made, generating monthly bills,

maintaining balances on prepaid calling cards, and storing information about

the communication networks.

• Finance: For storing information about holdings, sales, and purchases of ﬁnan-

cial instruments such as stocks and bonds.

• Sales:Forcustomer,product,andpurchaseinformation.

• Manufacturing: For management of supply chain and for tracking production

of items in factories, inventories of items in warehouses/stores, and orders for

items.

• Human resources: For information about employees, salaries, payroll taxes and

beneﬁts, and for generation of paychecks.

As the list illustrates, databases form an essential part of almost all enterprises today.

Over the course of the last four decades of the twentieth century, use of databases

grew in all enterprises. In the early days, very few people interacted directly with

database systems, although without realizing it they interacted with databases in-

directly—through printed reports such as credit card statements, or through agents

such as bank tellers and airline reservation agents. Then automated teller machines

came along and let users interact directly with databases. Phone interfaces to com-

puters (interactive voice response systems) also allowed users to deal directly with

databases—a caller could dial a number, and press phone keys to enter information

or to select alternative options, to ﬁnd ﬂight arrival/departure times, for example, or

to register for courses in a university.

The internet revolution of the late 1990s sharply increased direct user access to

databases. Organizations converted many of their phone interfaces to databases into

Web interfaces, and made a variety of services and information available online. For

instance, when you access an online bookstore and browse a book or music collec-

tion, you are accessing data stored in a database. When you enter an order online,

your order is stored in a database. When you access a bank Web site and retrieve

your bank balance and transaction information, the information is retrieved from the

bank’s database system. When you access a Web site, information about you may be

retrieved from a database, to select which advertisements should be shown to you.

Furthermore, data about your Web accesses may be stored in a database.

Thus, although user interfaces hide details of access to a database, and most people

are not even aware they are dealing with a database, accessing databases forms an

essential part of almost everyone’s life today.

The importance of database systems can be judged in another way—today, data-

base system vendors like Oracle are among the largest software companies in the

world, and database systems form an important part of the product line of more

diversiﬁed companies like Microsoft and IBM.

Silberschatz−Korth−Sudarshan:

Database System

Concepts, Fourth Edition

1. Introduction Text

Companies, 2001

1.2 Database Systems versus File Systems 3

1.2 Database Systems versus File Systems

Consider part of a savings-bank enterprise that keeps information about all cus-

tomers and savings accounts. One way to keep the information on a computer is

to store it in operating system ﬁles. To allow users to manipulate the information, the

system has a number of application programs that manipulate the ﬁles, including

• A program to debit or credit an account

• A program to add a new account

• A program to ﬁnd the balance of an account

• A program to generate monthly statements

System programmers wrote these application programs to meet the needs of the

bank.

New application programs are added to the system as the need arises. For exam-

ple, suppose that the savings bank decides to offer checking accounts. As a result,

the bank creates new permanent ﬁles that contain information about all the checking

accounts maintained in the bank, and it may have to write new application programs

to deal with situations that do not arise in savings accounts, such as overdrafts. Thus,

as time goes by, the system acquires more ﬁles and more application programs.

This typical ﬁle-processing system is supported by a conventional operating sys-

tem. The system stores permanent records in various ﬁles, and it needs different

application programs to extract records from, and add records to, the appropriate

ﬁles. Before database management systems

(DBMSs) came along, organizations usu-

ally stored information in such systems.

Keeping organizational information in a ﬁle-processing system has a number of

major disadvantages:

• Data redundancy and inconsistency. Since different programmers create the

ﬁles and application programs over a long period, the various ﬁles are likely

to have different formats and the programs may be written in several pro-

gramming languages. Moreover, the same information may be duplicated in

several places (ﬁles). For example, the address and telephone number of a par-

ticular customer may appear in a ﬁle that consists of savings-account records

and in a ﬁle that consists of checking-account records. This redundancy leads

to higher storage and access cost. In addition, it may lead to data inconsis-

tency; that is, the various copies of the same data may no longer agree. For

example, a changed customer address may be reﬂected in savings-account

records but not elsewhere in the system.

• Difﬁculty in accessing data. Suppose that one of the bank ofﬁcers needs to

ﬁnd out the names of all customers who live within a particular postal-code

area. The ofﬁcer asks the data-processing department to generate such a list.

Because the designers of the original system did not anticipate this request,

there is no application program on hand to meet it. There is, however, an ap-

plication program to generate the list of all customers. The bank ofﬁcer has

Silberschatz−Korth−Sudarshan:

Database System

Concepts, Fourth Edition

1. Introduction Text

Companies, 2001

4 Chapter 1 Introduction

now two choices: either obtain the list of all customers and extract the needed

information manually or ask a system programmer to write the necessary

application program. Both alternatives are obviously unsatisfactory. Suppose

that such a program is written, and that, several days later, the same ofﬁcer

needs to trim that list to include only those customers who have an account

balance of $10,000 or more. As expected, a program to generate such a list does

not exist. Again, the ofﬁcer has the preceding two options, neither of which is

satisfactory.

The point here is that conventional ﬁle-processing environments do not al-

low needed data to be retrieved in a convenient and efﬁcient manner. More

responsive data-retrieval systems are required for general use.

• Data isolation. Because data are scattered in various ﬁles, and ﬁles may be in

different formats, writing new application programs to retrieve the appropri-

ate data is difﬁcult.

• Integrity problems. The data values stored in the database must satisfy cer-

tain types of consistency constraints. For example, the balance of a bank ac-

count may never fall below a prescribed amount (say, $25). Developers enforce

these constraints in the system by adding appropriate code in the various ap-

plication programs. However, when new constraints are added, it is difﬁcult

to change the programs to enforce them. The problem is compounded when

constraints involve several data items from different ﬁles.

• Atomicity problems. A computer system, like any other mechanical or elec-

trical device, is subject to failure. In many applications, it is crucial that, if a

failure occurs, the data be restored to the consistent state that existed prior to

the failure. Consider a program to transfer $50 from account A to account B.

If a system failure occurs during the execution of the program, it is possible

that the $50 was removed from account A but was not credited to account B,

resulting in an inconsistent database state. Clearly, it is essential to database

consistency that either both the credit and debit occur, or that neither occur.

That is, the funds transfer must be atomic—it must happen in its entirety or

not at all. It is difﬁcult to ensure atomicity in a conventional ﬁle-processing

system.

• Concurrent-access anomalies.Forthesakeofoverallperformanceofthesys-

tem and faster response, many systems allow multiple users to update the

data simultaneously. In such an environment, interaction of concurrent up-

dates may result in inconsistent data. Consider bank account A, containing

$500. If two customers withdraw funds (say $50 and $100 respectively) from

account A at about the same time, the result of the concurrent executions may

leave the account in an incorrect (or inconsistent) state. Suppose that the pro-

grams executing on behalf of each withdrawal read the old balance, reduce

that value by the amount being withdrawn, and write the result back. If the

two programs run concurrently, they may both read the value $500, and write

back $450 and $400, respectively. Depending on which one writes the value

Silberschatz−Korth−Sudarshan:

Database System

Concepts, Fourth Edition

1. Introduction Text

Companies, 2001

1.3 View of Data 5

last, the account may contain either $450 or $400, rather than the correct value

of $350. To guard against this possibility, the system must maintain some form

of supervision. But supervision is difﬁcult to provide because data may be

accessed by many different application programs that have not been coordi-

nated previously.

• Security problems. Not every user of the database system should be able to

access all the data. For example, in a banking system, payroll personnel need

to see only that part of the database that has information about the various

bank employees. They do not need access to information about customer ac-

counts. But, since application programs are added to the system in an ad hoc

manner, enforcing such security constraints is difﬁcult.

These difﬁculties, among others, prompted the development of database systems.

In what follows, we shall see the concepts and algorithms that enable database sys-

tems to solve the problems with ﬁle-processing systems. In most of this book, we

use a bank enterprise as a running example of a typical data-processing application

found in a corporation.

1.3 View of Data

A database system is a collection of interrelated ﬁles and a set of programs that allow

users to access and modify these ﬁles. A major purpose of a database system is to

provide users with an abstract view of the data. That is, the system hides certain

details of how the data are stored and maintained.

1.3.1 Data Abstraction

For the system to be usable, it must retrieve data efﬁciently. The need for efﬁciency

has led designers to use complex data structures to represent data in the database.

Since many database-systems users are not computer trained, developers hide the

complexity from users through several levels of abstraction, to simplify users’ inter-

actions with the system:

• Physical level. The lowest level of abstraction describes how the data are actu-

ally stored. The physical level describes complex low-level data structures in

detail.

• Logical level. The next-higher level of abstraction describes what data are

stored in the database, and what relationships exist among those data. The

logical level thus describes the entire database in terms of a small number

of relatively simple structures. Although implementation of the simple struc-

tures at the logical level may involve complex physical-level structures, the

user of the logical level does not need to be aware of this complexity. Database

administrators, who must decide what information to keep in the database,

use the logical level of abstraction.

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