Part 1: Introduction
Junping Sun
Database Systems
1-1
Questions
1. What is a database?
2. What is a database system?
3. What is a database management system?
4. What type of data can a database management system handle?
5. What are the science and techniques of database management?
6. What are the most important issues in database systems?
7. What are these differences between database system approaches and
other approaches?
8. What is going on in the current database field?
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Database Systems
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Introduction
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Purposes and Objectives of Database Systems
Abstraction and View of Data
Data Models
Database Languages
Data Definition Language v.s. Data Manipulation Language
Transaction and Storage Management
Database Administrator and Users
Database System Architectures
Development of Database Systems and Current Trends
Issues in Database Systems and Applications
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Database Systems
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Database
Database:
•
A logical coherent collection of data with some inherent semantic
meaning.
From a system point of view:
•
A database is a collection of interrelated data in cluster format.
From a management point of view:
•
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A database is a collection of interrelated data that models an enterprise
activity.
A database contains information about one particular enterprise.
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Database Systems
Database System:
•
Database System = Databases + Database Management Systems
•
It is a collection of interrelated files and a set of programs that allow users
to access and modify these files
It provides a common repository to a group of interesting users to access
the data in the database.
It is a computerized data keeping system.
Database systems are designed to manage large bodies of information.
A database system must provide for the safety of the information stored,
despite system crashes or attempts at unauthorized access.
If data are to be shared among several users, the system must avoid
possible anomalous results.
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Database Systems
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Database Management Systems
Database Management System:
•
A software subsystem managing databases
It enables concurrent users to create, operate, and maintain a database.
It offers data definition and manipulation facilities.
•
It is an interface between the computer operating system and a database
system,
•
It is also an interface between database end users and the database
system.
•
The primary goal of the database management system (DBMS) is to
provide an environment that is both convenient and efficient to use in
retrieving and storing database information.
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Database Systems
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Database Management System as an Interface
Applications
.....
.....
System Software
.....
.....
DBMS
Others
.....
.....
Operating Systems
.....
Computer Hardware
Database Systems
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A Simplified Database System Environment
Users/Programmers
Application Programs/Queries
DBMS
SOFTWARE
SOFTWARE TO PROCESS
QUERIES/PROGRAMS
SOFTWARE TO ACCESS
STORED DATA
Stored
Database
Definition
Stored
Databases
META-DATA
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Database Systems
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Physical Centralized Database Architecture
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Database Systems
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Simplified Logical Client-Server Architecture
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Database Systems
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Simplified Logical Client-Server Architecture
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Database Systems
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Purposes of Database Systems
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Database systems were developed to handle the following difficulties of
typical file-processing systems supported by conventional operating
systems.
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Data redundancy and inconsistency
Difficulty in accessing data
Data isolation - multiple files and format
Integrity problems
Atomicity of updates
Concurrency access by multiple users
Security problems
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Data Abstraction and View of Data
Objectives of Database Systems:
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A major purpose of a database system is to provide users with an
abstract view of the data.
•
The system hides certain details of how the data are stored and
maintained.
•
For the database system to be usable, it must retrieve data efficiently.
This concern has led to the design of complex data structures (internal)
for the representation of data in the database.
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Since many database-system end users are not computer trained,
developers hide the complexity from users through several levels of
abstraction, to simplify users’ interactions with the system.
Database Systems
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The Three Levels of Data Abstraction
View Level
view 1
view 2
. . .
view n
Logical Level
Physical Level
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Physical Level
Physical Level:
• The lowest level of abstraction describes how the data are actually
stored.
• At the physical level, complex low-level data structures are described in
details.
• It uses the physical data model to describe the complete details of data
storage structures, access paths to the database, and how the data are
distributed in the address space.
Record Format and Data Blocking:
• Fixed length record v.s. variable length
• Spanned v.s. unspanned
File Organization and Access Paths:
• Sequential v.s. random (hashing)
• Indices: static v.s. dynamic, balanced v.s. unbalanced, single dimension
v.s. multi-dimension.
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Database Systems
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Logical Level
Logical Level:
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It describes what data are stored in the database, and what relationships
(logical) exist among those data.
•
The entire database is thus described in terms of a small number of
relatively simple structures.
•
Although the implementation of the simple data structures at the logical
level may involve complex physical-level structures, the database end
users of logical level do not necessarily need to be aware of this
complexity.
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The logical level of abstraction is used by database administrators, who
must decide what information is to be stored in the database.
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Database Systems
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View Level
View Level:
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The highest level of abstraction describes only part of the entire
database.
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Despite of the use of simpler structures at the logical level, some
complexity remains, because of the large size of the database.
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Many users of the database system will not be concerned with all the
information. Since such users need to access only a part of the database.
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The interaction between each group of users and the database system is
simplified, the view level of abstraction is defined.
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A database system may provide many views for the same database.
Database Systems
Junping Sun
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Three Levels of Database Architecture (ANSI/SPARC)
End Users
VIEW LEVEL
EXTERNAL
VIEW1
...
EXTERNAL
VIEWN
mapping (m:n)
view/logical
LOGICAL LEVEL
LOGICAL SCHEMA
mapping (1:1)
logical/physical
PHYSICAL LEVEL
PHYSICAL SCHEMA
Stored Databases
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An Example of the Three Levels
External (PL/1)
DCL
1
EMPP,
2
EMP# CHAR(6),
2
SAL FIXED BIN(31);
External (COBOL)
01
EMPC.
02 EMPNO PIC X(6).
02 DEPTNO PIC X(4).
Logical
EMPLOYEE
EMPLOYEE_NUMBER
DEPARTMENT_NUMBER
SALARY
CHARACTER (6)
CHARACTER (4)
NUMERIC (5)
Physical
STORED_EMP LENGTH = 18
PREFIX TYPE = BYTE(6), OFFSET = 0
EMP# TYPE = BYTE(6), OFFSET = 6, INDEX = EMPX
DEPT# TYPE = BYTE(4), OFFSET = 12
PAY
TYPE = FULLWORD, OFFSET = 16
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Database Systems
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Database Instances
Database Instances:
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The collection of information stored in the database at a particular
moment (a particular time point) is called database instances or database
status.
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The actual content of the database at a particular point in time.
•
Databases change over time as information is inserted, deleted, and/or
updated.
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Database Schema
Database Schema:
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•
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The overall design of a database is called the database schema. It is the
logical structure of the database. The schema are changed infrequently.
A database schema corresponds to the programming language type
definition.
A variable of a given type has a particular value at a given instant. The
value of a variable in programming language corresponds to an instance
of a database schema.
Database Schemas at Three Levels:
• Each database has physical schema, logical schema and subschema.
• Database systems support one physical schema, one logical schema,
several subschemas.
Database Systems
Junping Sun
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Database Hierarchy Structure
User Level Database
User Group 1
User Group 2
.....
User Group n
Subschema 1
Subschema 2
.....
Subschema n
User View
External Schema
Subschema to Conceptual Schema Mapping
Conceptual Level Database
DBMS
DBA View
Database Schema
Conceptual/Logical Schema
Conceptual to Internal Mapping
Physical Level Database
OS
System Programmer View
Internal/Physical Schema
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Storage Schema
Database Systems
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Data Independence
Data Independence:
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The ability to modify a schema definition at one level without affecting a
schema definition at the next higher level is called data independence.
Physical Data Independence:
• The ability to modify the physical schema without causing modifications
of both logical schema and application programs.
• Modifications at the physical level are occasionally necessary to improve
database performance.
Logical Data Independence:
• The ability to modify the logical schema without causing application
programs to be rewritten.
• Modifications at the logical level are necessary whenever the logical
structure of the database is altered.
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Data Models
Data Model:
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Data Model = Schema + Operations + Constraints
A collection of tools for describing:
data, data relationship, data semantics, and data constraints
Underlying the structure of a database is the data model.
A set of concepts that can be used to describe the structure of a
database.
A collection of conceptual tools for describing data, data relationships,
data semantics, consistency constraints.
The various data models that have been proposed fall into three groups:
object-based logical models
record-based logical models
physical models
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Object-Based Logical Models
Object-Based Logical Models:
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Object-based logical models are used in describing data at the logical
and view levels.
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They are characterized by the fact that they provide fairly flexible
structuring capabilities and allow data constraints to be specified
explicitly.
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Several of the more widely known ones are
The entity-relationship model [Chen 1976]
The object-oriented model [Kim 1990b]
The semantic data model [Hull and King 1987]
The functional data model [Sibley and Kerschberg 1977][Shipman 1981]
Database Systems
Junping Sun
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A Sample E-R Diagram
social-security
customer-street
account-number
customer-name
customer
Junping Sun
balance
customer-city
depositor
Database Systems
account
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Record-Based Logical Models
Record-Based Logical Models:
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Record-based logical models are used in describing data at the logical
and view levels.
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In contrast to object-based data models, they are used both to specify
the overall logical structure of the database and to provide a higher-level
description of the implementation.
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Record-based models are so named because the database is structured
in fixed-format records of several types. Each record type defines a fixed
number of fields, or attributes, and each field is usually of a fixed length.
•
The simplicity of record-based logical model is in contrast to many of the
object-based models, whose richer structure often leads to variablelength records at the physical level.
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Database Systems
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Relational Data Model:
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Relational Model, Network Model, Hierarchical Model are three most
widely accepted record-based logical data models.
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The relational model differs from the network and hierarchical models in
that it does not use pointers or physical links.
•
The relational model relates records by the values they contain in each of
tables.
This freedom from the use of pointers allows a formal mathematical
foundation to be defined.
Physical Data Model:
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They are used to describe data at the lowest level. Physical data models
capture aspects of database system implementation.
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Database Systems
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A Sample Relational Database
customer-name social-security customer-street customer-city account-number
Johnson
Smith
Hayes
Turner
Johnson
Jones
Lindsay
Smith
192-83-7465
019-28-3746
677-89-9011
182-73-6091
192-83-7465
321-12-3123
336-66-9999
019-28-3746
Alma
North
Main
Putnam
Alma
Main
Park
North
Palo Alto
Rye
Harrison
Stamford
Palo Alto
Harrison
Pittsfield
Rye
A-101
A-215
A-102
A-201
A-201
A-217
A-222
A-201
Database Systems
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A Sample Network Database
A-101 500
Johnson
192-83-7456
Alma
Palo Alto
Smith
019-28-3746
North
Rye
Hayes
677-89-9011
Main
Jarrison
Tumer
182-73-6091 Putnam Stamford
Jones
321-12-3123 Main
Harrison
Lindsay
336-66-9999
Pittsfiel
Junping Sun
Park
Database Systems
A-215 700
A102 400
A-305 350
A-201 900
A-217 750
A-222 700
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A Sample Hierarchical Database
Johnson 192-83-7465 ...
Smith
019-28-3746 ...
Hayes 677-89-9
...
Tumer 182-73-609 ...
Jones 321-12-3123 ...
A-101 500
A-201 900
Lindsay 336-66-9999 ...
A-102 400
A-217 750
A-215 700
A-201 900
A-305 350
A-222 700
Database Systems
Junping Sun
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Database Languages
Database Languages:
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It is a description and implementation of data models.
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It is an interface between database users and a database system.
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Database Language = Database Definition Language (DDL) +
Database Manipulation Language (DML)
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DDL defines database schema
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DML describes database operations such as
Queries, insertion, deletion, and update
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Database Systems
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Data Definition Language
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•
A database schema is specified by a set of definitions expressed by a
special language called a data definition language.
The result of compilation of DDL statements is a set of tables that is
stored in a special file called data dictionary or data directory.
Data Dictionary:
• It is a file that contains meta-data - that is, the data about data
(description of data).
• The data dictionary is consulted before actual data are read or modified
in the database.
Data Storage and Definition Language:
• The storage structure and access methods used by the database system
are specified by a set of definitions in a special type of DDL called data
storage and definition language.
• The result of compilation of these definitions is a set of instructions to
specify the implementation details of the database schemas.
Database Systems
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Data Manipulation Language
Data Manipulation:
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The retrieval of information stored in the database
The insertion of new information into the database
The deletion of information from the database
The modification (update) of information stored in the database
Data Manipulation Language:
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•
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It is a language that enables users to access or manipulate data as
organized by the appropriate data model.
A query is a statement requesting the retrieval of information. The
portion of a DML that involves information retrieval is called a query
language.
It is common practice to use the terms query language and data
manipulation language synonymously.
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DML- Procedural v.s. Non-Procedural Language
There are basically two types of DMLs:
Procedural Data Manipulation Languages:
• They require a user to specify both what data are needed how to get
those data.
• Most procedural DMLs are set of procedural call statements and must be
embedded in a general purpose programming language.
• Procedural DMLs need to make use of programming language constructs
such as looping, if.. then.
Non-Procedural Data Manipulation Languages:
• They require a user to specify what data are needed without specifying
how to get those data.
• Non-procedural DML statements can be either entered interactively or be
embedded in a general purpose programming language.
Database Systems
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Transaction Management
Transaction:
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A transaction is a collection of operations that performs a single logical
function in a database application.
The execution of a program that includes database access operations.
Each transaction is a unit of both atomicity and consistency.
Transaction Management:
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The transaction management components in a 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.
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Properties of Transactions (ACID)
•
To ensure integrity of the data, it is required that the database system
maintains the following properties of the transactions.
Atomicity:
• A transaction is an atomic unit of processing; it is either performed in its
entirety or not performed at all.
Consistency:
• A correct execution of the transaction must take the database from one
consistent state to another.
Isolation:
• A transaction should not make its updates visible to other transactions
until it is committed. Although multiple transactions may execute
concurrently, the system guarantees that each transaction is unaware of
other transactions executing concurrently.
Durability:
• Once a transaction changes the database and the changes are
committed, these changes must never be lost because of subsequent
failures.
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Database Systems
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Storage Management
Storage Manager:
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A 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 the following tasks:
interaction with the file manager
efficient storing, retrieving, and updating of data
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Database Systems
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Event Sequences of Record Retrieval in an Application
Application
Program
2
11
Application Program
Subschema
1
Status
User Work Area
10
3
Schema
DBMS
9
System Buffer
8
5
4
6
7
Operating
System
Database
Junping Sun
Physical Storage Schema
Database Systems
1-39
Event Sequences of Record Retrieval in an Application
1. Application program sends a request to read a record. Program provides the
search key, data type and others.
2. DBMS checks the subschema used by program A and data type.
3. DBMS looks up the global database schema (conceptual/logical schema) and
determine the required items.
4. DBMS looks up the physical storage schema description and decides which
record to be retrieved.
5. DBMS sends request to operating system and indicates the requested
record.
6. Operating system retrieve the requested record from storage device.
7. The requested record is sent to system buffer from storage device.
8. DBMS compares subschema and schema and determines the required items,
DBMS transforms the data record in schema format to subschema format.
9. DBMS sends the data in system buffer to program user work area.
10.DBMS provides application program with DB_status value and also if any
errors.
11.Then application program can use and process the data.
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Database Systems
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Event Sequences from Different View
AP1
Application
Programmer View
S
UWA
AP2
......
S
UWA
AP1
Subschema
DBMS
DBA View
AP2
Subschema
....
Schema
Systems Buffer
OS
System
Programmer View
Junping Sun
Database
Physical Storage
Schema
Database Systems
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DBMS Capabilities
•
Persistence
•
The ability of data to persist through different program invocation.
Secondary storage management
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•
Transactions
DBMS should support a sequence of primitive atomic reads and writes
against the database.
Concurrency control
DBMS should support transactions of multiple users currently accessing
the database.
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Recovery
It is necessary to restore the database to a consistent state after crashes.
•
Ad hoc query facility
The facility should be reasonably declarative.
•
•
Security
Integrity
•
DBMS map one consistent state onto another
Performance
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Database Administrator
Database Administrator:
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Coordinates all the activities of the database system;
The database administrator has a good understanding of the information
resources and needs in an enterprise.
The Duties of Database Administrators:
•
•
•
•
•
•
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Schema definition
Storage structure and access method definition
Schema and physical organization modification
Granting user authority to access the database
Specify integrity constraints
Acting as liaison with users
Monitoring performance and responding to changes in requirements
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Database Systems
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Database Users
•
Users are differentiated by the way they expect to interact with the
system
Application Programmers:
• Interact with system through DML
Sophisticated Users:
• Form requests in a database query language
Specialized Users:
• Write specialized database applications that do not fit into the traditional
data processing framework
Naive Users:
• Invoke one of the permanent application programs that have been written
previously
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Database Systems
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Classifications of Database Management Systems
Classification Based on Database Models:
Hierarchical, Network, Relational, Object-Oriented DBMS
Classification Based on the Number of Users:
Single User V.S. Multi-users DBMS
Classification Based on the Number of Sites:
Centralized V.S. Distributed DBMS
Classification Based on Geographical Locations:
Local v.s. Long Haul DBMS
Classification Based on the Type of Databases Involved:
Homogeneous V.S. Heterogeneous DBMS
Classification Based on the Autonomous Capability:
Non-Federated V.S. Federated DBMS
Classification Based on the Type of Media:
Single or Simple Media V.S. Multimedia DBMS
Classification Based on the Time and Dimension Space:
Temporal DBMS and Spatial DBMS
Classification Based on the Extensibility:
Closed vs. Open DBMS
Database Systems
Junping Sun
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The Evolution of Databases
File Systems
Network
Hierarchical
Relational
Object-Oriented
Languages
Semantic Models
Complex Object Models
Object-Oriented Databases
Hypermedia
Information Retrieval
Artificial
Intelligence
Intelligent Databases
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Database Systems
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23
Generations of Database Systems
1. File System: ISAM (Index Sequential Access Methods)
VSAM (Virtual Storage Access Methods)
2. Hierarchical Database Systems
IMS/VS (Information Management System//Virtual Storage)
IMS DB/DC (Database/Data Communication)
3. Network Database Systems
CODASYL DBTG
(Conference on Data Systems and Languages Database Task Group)
4. Relational Database Systems
Relational Data Model by E. F. Codd in 1970
System R, INGRES, System 2000 after 1976
5. Next Generation Database Systems
Object-Relational Databases v.s. Object-Oriented Databases
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Database Systems
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Evolution of Database Systems
Evolution from File Management Systems to DBMS
• Separation of Data Description and Data Manipulation
• Data Integrity, Sharing, and Security
• Minimal Redundancy and Storage Space
• Easy Data Administration and Control
Evolution from Network and Hierarchical DBMS to Relational DBMS
• Logical and Physical Data Independence
• Procedural to Nonprocedural Interfaces Evolution
Navigation to Non-navigation
• Enriched Data Model Based on Predicate Logic Concept
Evolution from Non-Object-Oriented DBMS to Object-Oriented DBMS
• Traditional Database Applications to Non-traditional Database
Applications
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Database Systems
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New Database Applications
CAD/CAE/CAM/CAP/CASE/CIM Databases
Cartographical and Geological Databases
Data Intensive Knowledge Based Systems
Geographical Databases and Information Systems
Historical Databases
Graphical, Image, Pictorial and Visual Databases
Office Automation and Office Information Systems
Real Time Database Systems
Scientific Database and Medical Applications
Genomic Databases
Organic Compound, Spectral Analysis, Genetic Encoding
Chromatography Patterns
Software Engineering Databases
Configuration and Project Management
Statistical Databases
System Services and Network Management and Modeling
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Database Systems
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Comparative View of Different Data Processing Approaches
Software Engineering with Programming Languages:
• Abstract Data Type
Data Structure + Operations
• Object-Oriented Programming Languages:
Class + Messages
Artificial Intelligence
• Declarative Knowledge v.s. Procedural Knowledge
• Extensional Knowledge (Facts) v.s. Intensional Knowledge (Rule)
Database Management Systems:
• Schema (Data Definitions) and Operations (Data Manipulations)
Comparison
• Main memory based search methods v.s. secondary based search
methods
• Functional based v.s. data organization oriented
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Database Systems
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Issues in Database Systems
Database Design:
Conceptual Design
• It produces a high-level, abstract representation of reality (mini-world).
Logical Design
• It translates this representation into specifications that can be
implemented on and processed by a computer system.
Physical Design
• It determines the physical storage structures and access methods
required for efficient access to the contents of a database from
secondary storage device.
• It depends on the DBMS.
Database Management System Design:
• To design a system software to provide the user with a means of
communicating with the database efficiently.
• DBMS is an implementation data model oriented system.
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Database Systems
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Phases of Database Design for Large Databases
Stage 1:
Requirements
Collections and Analysis
Data Requirements
Processing Requirements
Stage 2:
Conceptual Design
Conceptual &
External Schema Design
(DBMS-Independent)
Transaction Design
(DBMS-Independent)
Stage 3:
Data Model
Conceptual &
Stage 4:
Physical Design
Frequencies
performance constraints
Internal Schema Design
(DBMS-Dependent)
Stage 5:
Implementation
DML Statements
Junping Sun
Database Systems
Implementation
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26
Database Design Stages
Data Processing
Requirements
Information
Requirements
Requirement Analysis
Stage I
Requirement
Specification
Conceptual Design
DBMS
Characteristics
Stage II
Information
Structure
Implementation Design
Stage III
Hardware/Operating
System Characteristics
Logical Database
Structure
Physical Design
Stage IV
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Important Issues in Database System Domain
Semantics of Database Systems:
•
A database should be correctly designed in terms of database
application semantics at the logical level.
Performance of Database Systems:
•
A database system should be able to provide the quickest response to
any type of user queries.
•
This requires the database schema is optimally designed at both the
logical level (database modeling) and physical level (database tuning).
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Database Systems
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Hierarchy of Data Types
5th Normal Form
4th Normal Form
Boyce-Codd Normal Form
3rd
Relational DBMS
Normal Form
2nd Normal Form
Object-Oriented DBMS
1st Normal Form
Non First Normal Form (NF2)
Semi-Structural Data
(Hypermedia/Hypertext)
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Database Systems
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Issues in Applications of Computer Information Systems
Data Processing (Search)
Correct, Efficiency and User Friendly
Information Storage and Retrieval
Search Algorithms & Access Mechanisms
Data Structures
Physical Storage
Computer Hardware
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Database Technology
Database Technology:
•
It is a comprehensive application of computer science and other
technologies.
Compiler
Data Structures & Algorithms
Operating Systems
System Analysis, Modeling and Design
Software Engineering
AI and Expert Systems
Optimization Theory
User Interface and Human Factors
Network and Distributed Systems
Mathematical Predicate Logic
Junping Sun
Database Languages
Storage Structures & Data Access
Concurrency Control
Database Modeling and Design
DB & DBMS Development
Heuristic Search and DDS
Query Optimization
Database Interfaces (GUI)
Distributed Database Systems
Database Theory
Database Systems
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Current Trends of Database Systems
•
From the Simple Data Model to the Complex Object Data Model
Pure Object-Oriented Data Model v.s. Relational-Object Data Model
•
From Discrete Data Model to Probabilistic Data Model
•
From Simple/Single Media Data to Multimedia/Hypermedia Data
•
From Structural Data to Semi-Structural Data
•
From Single Database to Multidatabase Systems
(Homogenous v.s. Heterogeneous)
Data Warehousing
•
From Single Dimensional Applications to Multidimensional Applications
(On Line Transaction Processing v.s. On Line Analytical Processing)
Junping Sun
Database Systems
1-58
29
Current Trends of Database Systems
•
From Data Query to Data Mining and Knowledge Query
•
From Simple Text-based Database User Interfaces to Intelligent
Graphical User Interfaces
•
From Centralized Database Systems to Distributed/Parallel Database
Systems
(Internet v.s. Intranet)
•
From Single Processor Computer (Server) to Multiple Processor
Computer System (Server)
•
From Single Tier to Multiple Tiers
•
From Fat Client Applications to Thin Client Applications
Junping Sun
Database Systems
1-59
Database and DBMS Revisited
•
Programs = Data Structures + Algorithms
Nicklaus Wirth
•
Database System = Databses + Database Management System(s)
•
Database Management System =
Junping Sun
Data Model +
Data Structures +
Algorithms
Database Systems
1-60
30