DATA MODEL - Department of Computer Science
Download
Report
Transcript DATA MODEL - Department of Computer Science
CS157A Lecture 2
DB Mangement Systems
Prof. Sin-Min Lee
Department of Computer Science
San Jose State University
Chapter 1: Introduction
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
Database System Concepts
1.2
©Silberschatz, Korth and Sudarshan
1. Database Theory
Why use database?
Data is a valuable corporate resource which needs adequate, accuracy,
consistency and security controls.
The centralised control of data means that for many applications the data
will already exist, and facilitate quicker development.
Data will no longer be related by application programs, but by the
structure defined in the database.
Easier to maintain systems
Database System Concepts
1.3
©Silberschatz, Korth and Sudarshan
Traditional File Systems
In the the past as new applications were written they used existing
files, or created a new file for their use.
Sometimes several existing files need to be sorted and merged to
obtain the new file.Thus, it is probable that several files will contain the
same information stored in different ways. In other words, there will be
redundant and possibly inconsistent data.
Consider the files for an insurance company
POLICY#
POLICYHOLDER
data ADDRESS
PREMIUM-PA
PREMIUM-TOTAL
PREMIUMS
POLICY#
POLICYHOLDER
data ADDRESS
AGENT-CODE
RENEWAL-DATE
RENEWAL-AMT
AGENCY
Database System Concepts
1.4
©Silberschatz, Korth and Sudarshan
Traditional File Systems
Applications were often considered in relative isolation.
Data that should have been together was not.
The potential for flexible enquiry and reporting was limited.
All validations were in the programs.
Procedures were required to for backup and recovery.
All programmers had access to all records.
There was limited concurrent access.
Database System Concepts
1.5
©Silberschatz, Korth and Sudarshan
Basic Definitions
Database: A collection of related data
Data: Known facts that can be recorded
Schema: Some part of the real world about which data
is stored in the database.
Database Management System(DBMS):
A software package to facilitate the creation and
maintenance of a computerised database.
Database System Concepts
1.6
©Silberschatz, Korth and Sudarshan
Degrees of Data Independence
·
Device Characteristics
·
Blocking Factors
·
Data Access Organisation
·
Physical Record Location
·
Logical Views (Local)
·
Virtual Data Items
·
Virtual Records
·
Data Value Characteristics
·
Data Element Name Only
Database System Concepts
1.7
©Silberschatz, Korth and Sudarshan
Logical vs Physical Data Independence
Application
Program
Local Views
Database System Concepts
GLOBAL
LOGICAL
DATABASE
DESCRIPTION
Physical
Files
Logical Data
Physical Data
Independence
Independence
1.8
©Silberschatz, Korth and Sudarshan
Three Schema Architecture
ANSI & ISO suggest that DBMS should have three schemas
·
CONCEPTUAL SCHEMA - the global logical model of the data and
processing of the enterprise. i.e community user view.
·
EXTERNAL SCHEMA(S) - the logical application views of the CS. i.e
individual user views.
·
INTERNAL SCHEMA - internal level storage view.
Database System Concepts
1.9
©Silberschatz, Korth and Sudarshan
Three Schema Architecture
External
Schema 1
External
Schema 2
External
Schema n
Conceptual
Schema
Internal
Schema
Database System Concepts
1.10
©Silberschatz, Korth and Sudarshan
The External Level
·
Each user has a language through which they access or see the
database.
·
For the programmer - COBOL etc, for the end-user a query
language or special purpose language.
·
All languages will contain a data sub-language which may be
tightly or loosely coupled to the host language.
Database System Concepts
1.11
©Silberschatz, Korth and Sudarshan
·
DSLs generally contain a data definition language DDL and data
manipulation language DML.
Database System Concepts
1.12
©Silberschatz, Korth and Sudarshan
The Conceptual Level
·
A representation of the entire information content of the database.
·
Defined with a Conceptual Schema Language which does not
represent any storage or access details.
·
Should include all security and integrity rules and some suggest
the CS should describe the total enterprise including all allowable
processing.
Database System Concepts
1.13
©Silberschatz, Korth and Sudarshan
The Internal Level
·
Low level representation of entire database.
·
Deals with stored records rather than conceptual or external
records.
·
Stored records may differ in structure from conceptual records
and external records.
·
The Internal Schema is still one level away from physical records
which are often called pages or blocks
Database System Concepts
1.14
©Silberschatz, Korth and Sudarshan
Inter-Related Data
CLAIMS
RENEWALS
D
B
M
S
RENEWALS
CLAIMS AGENCY
AGENCY
Data related by structure
Flexible enquiry easier
Database System Concepts
QUERY
1.15
©Silberschatz, Korth and Sudarshan
Multiple Applications
DATABASE
LOCAL
VIEWS
AGENCY
CLAIMS
RENEWALS
Database System Concepts
1.16
©Silberschatz, Korth and Sudarshan
Database Management System (DBMS)
Collection of interrelated data
Set of programs to access the data
DBMS contains information about a particular enterprise
DBMS provides an environment that is both convenient and
efficient to use.
Database Applications:
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
Databases touch all aspects of our lives
Database System Concepts
1.17
©Silberschatz, Korth and Sudarshan
Purpose of Database System
In the early days, database applications were built on top of
file systems
Drawbacks of using file systems to store data:
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 formats
Integrity problems
Integrity constraints (e.g. account balance > 0) become part
of program code
Hard to add new constraints or change existing ones
Database System Concepts
1.18
©Silberschatz, Korth and Sudarshan
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
Database System Concepts
1.19
©Silberschatz, Korth and Sudarshan
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.
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.
Database System Concepts
1.20
©Silberschatz, Korth and Sudarshan
View of Data
An architecture for a database system
Database System Concepts
1.21
©Silberschatz, Korth and Sudarshan
Instances and Schemas
Similar to types and variables in programming languages
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 point in time
Analogous to the value of a variable
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.
Database System Concepts
1.22
©Silberschatz, Korth and Sudarshan
Data Models
A collection of tools for describing
data
data relationships
data semantics
data constraints
Entity-Relationship model
Relational model
Other models:
object-oriented model
semi-structured data models
Older models: network model and hierarchical model
Database System Concepts
1.23
©Silberschatz, Korth and Sudarshan
What is a Database Management System?
1. Manages very large amounts of data.
2. Supports efficient access to very large amounts of data.
3. Supports concurrent access to very large amounts of data.
Example: bank and its ATM machines.
4. Supports secure, atomic access to very large amounts of
data.
Contrast two people editing the same UNIX file – last to write “wins” – with
the problem if two people deduct money from the same account via ATM
machines at the same time – new balance is wrong whichever writes last.
Database System Concepts
1.24
©Silberschatz, Korth and Sudarshan
Relational Model
Based on tables, as:
acct #
name
balance
12345
Sally
1000.21
34567
Sue
285.48
…
…
…
Today used in most DBMS's.
Database System Concepts
1.25
©Silberschatz, Korth and Sudarshan
The DBMS Marketplace
Relational DBMS companies – Oracle, Sybase – are among the largest software
companies in the world.
IBM offers its relational DB2 system. With IMS, a nonrelational system, IBM is
by some accounts the largest DBMS vendor in the world.
Microsoft offers SQL-Server, plus Microsoft Access for the cheap DBMS on the
desktop, answered by “lite” systems from other competitors.
Relational companies also challenged by “object-oriented DB” companies.
But countered with “object-relational” systems, which retain the relational core
while allowing type extension as in OO systems.
Database System Concepts
1.26
©Silberschatz, Korth and Sudarshan
Three Aspects to Studying DBMS's
1. Modeling and design of databases.
Allows exploration of issues before committing to an implementation.
2. Programming: queries and DB operations like update.
SQL = “intergalactic dataspeak.”
3. DBMS implementation.
CS180 = (1) + (2), while (3) is covered partly in CS277.
Database System Concepts
1.27
©Silberschatz, Korth and Sudarshan
Query Languages
Employee
Name
Dept
Department
Dept
Manager
SQL
SELECT Manager
FROM Employee, Department
WHERE Employee.name = "Clark Kent”
AND Employee.Dept = Department.Dept
Query Language
Data definition language (DDL) ~ like type defs in C or
Pascal
Data Manipulation Language (DML)
Query (SELECT)
UPDATE < relation name >
SET <attribute> = < new-value>
WHERE <condition>1.28
Database System Concepts
©Silberschatz, Korth and Sudarshan
Host Languages
C, C++, Fortran, Lisp, COBOL
Application prog.
Calls to
DB
DBMS
Local Vars
(Memory)
(Storage)
Host language is completely general (Turing complete)
but gives you no support
Query language—less general "non procedural" and
optimizable
Database System Concepts
1.29
©Silberschatz, Korth and Sudarshan
Relational model is good for:
Large amounts of data —> simple operations
Navigate among small number of relations
Difficult Applications for relational model:
VLSI Design (CAD in general)
CASE
• Graphical Data
ALU
ADDER
A
FA
CPU
Adder
ALU
ADDER
Bill of Materials or
transitive closure
Database System Concepts
1.30
©Silberschatz, Korth and Sudarshan
Where number of "relations" is large, relationships are
complex
•Object Data Model
•Logic Data Model
OBJECT DATA MODEL
1. Complex Objects – Nested Structure (pointers or
references)
2. Encapsulation, set of Methods/Access functions
3. Object Identity
4. Inheritance – Defining new classes like old classes
Object model: usually find objects via explicit navigation
Also query language in some systems
Database System Concepts
1.31
©Silberschatz, Korth and Sudarshan
LOGIC (Horn Clause) DATA MODEL
• Prolog, Datalog
if A1 and A2 then B
prolog B:- A1 and A2
Functions s(5) = 6 (successor)
Predicates with Arguments sum(X,Y,Z) X + Y = Z
sum(X,0,X) means X + 0 = X (always true for all X)
sum(X,s(Y),s(Z)):-sum(X,Y,Z)
means X+(Y+1) = (Z+1) if X + Y = Z
More power than relational
Can Compute Transitive Closure
edge(X,Y)
path(X,Y) :- edge(X,Y)
path(X,Z) :- path(X,Y) & edge(Y,Z)
Database System Concepts
1.32
©Silberschatz, Korth and Sudarshan
60’s
Hierarchical
Network
70's
80's
Choice for most new
applications
Relational
90’s
Object Bases
Knowledge Bases
now
Database System Concepts
1.33
©Silberschatz, Korth and Sudarshan
Entity-Relationship Model
Example of schema in the entity-relationship model
Database System Concepts
1.34
©Silberschatz, Korth and Sudarshan
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
Database System Concepts
1.35
©Silberschatz, Korth and Sudarshan
Relational Model
Attributes
Example of tabular data in the relational model
Customerid
customername
192-83-7465
Johnson
019-28-3746
Smith
192-83-7465
Johnson
321-12-3123
Jones
019-28-3746
Smith
Database System Concepts
customerstreet
customercity
accountnumber
Alma
Palo Alto
A-101
North
Rye
A-215
Alma
Palo Alto
A-201
Main
Harrison
A-217
North
Rye
A-201
1.36
©Silberschatz, Korth and Sudarshan
A Sample Relational Database
Database System Concepts
1.37
©Silberschatz, Korth and Sudarshan
Data Definition Language (DDL)
Specification notation for defining the database schema
E.g.
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 (i.e., 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
Database System Concepts
1.38
©Silberschatz, Korth and Sudarshan
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 query language
Database System Concepts
1.39
©Silberschatz, Korth and Sudarshan
SQL
SQL: widely used non-procedural language
E.g. find the name of the customer with customer-id 192-83-7465
select customer.customer-name
from customer
where customer.customer-id = ‘192-83-7465’
E.g. find the balances of all accounts held by the customer with
customer-id 192-83-7465
select account.balance
from depositor, account
where depositor.customer-id = ‘192-83-7465’ 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
Database System Concepts
1.40
©Silberschatz, Korth and Sudarshan
Database Users
Users are differentiated by the way they expect to interact with
the system
Application programmers – interact with system through DML
calls
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
Naïve 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
Database System Concepts
1.41
©Silberschatz, Korth and Sudarshan
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
Database System Concepts
1.42
©Silberschatz, Korth and Sudarshan
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.
Concurrency-control manager controls the interaction among the
concurrent transactions, to ensure the consistency of the
database.
Database System Concepts
1.43
©Silberschatz, Korth and Sudarshan
Storage Management
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 to the following tasks:
interaction with the file manager
efficient storing, retrieving and updating of data
Database System Concepts
1.44
©Silberschatz, Korth and Sudarshan
Overall System Structure
Database System Concepts
1.45
©Silberschatz, Korth and Sudarshan
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”
Database System Concepts
1.46
©Silberschatz, Korth and Sudarshan