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1-1
What is “Data”?
 
ANSI definition:
¡
Data
¢
A representation of facts, concepts, or instructions in a
formalized manner suitable for communication, interpretation,
or processing by humans or by automatic means.
£
Any representation such as characters or analog quantities to
which meaning is or might be assigned. Generally, we perform
operations on data or data items to supply some information
about an entity.
 
Volatile vs. persistent data
¡
Our concern is primarily with persistent data
1-2
Early Data Management -
Ancient History¤
Data are not stored on disk
¤
Programmer defines both logical data structure and physical
structure (storage structure, access methods, I/O modes, etc)
¤
One data set per program. High data redundancy.
PROGRAM 2
Data
Management
PROGRAM 3
Data
Management
PROGRAM 1
Data
Management
DATA SET 1
DATA SET 2
DATA SET 3
1-3
Problems
¥
There is no persistence.
¦
All data is transient and disappears when the program
terminates.
¥
Random access memory (RAM) is expensive and
limited
¦
All data may not fit available memory
¥
Programmer productivity low
¦
The programmer has to do a lot of tedious work.
1-4
File Processing -
Recent (and Current) History§
Data are stored in files with interface between programs and
files.
§
Various access methods exist (e.g., sequential, indexed, random)
§
One file corresponds to one or several programs.
PROGRAM 1
Data
Management FILE 1
FILE 2
RedundantData
PROGRAM 2
Data
Management
PROGRAM 3
Data
Management
File
System
Services
1-5
File System Functions
¨
Mapping between logical files and physical files
©
Logical files: a file viewed by users and programs.

Data may be viewed as a collection of bytes or as a collection
of records (collection of bytes with a particular structure)

Programs manipulate logical files
©
Physical files: a file as it actually exists on a storage
device.

Data usually viewed as a collection of bytes located at a
physical address on the device

Operating systems manipulate physical files.
¨
A set of services and an interface (usually called
application independent interface – API)
1-6
Problems With File Systems
¨
Data are highly redundant
©
sharing limited and at the file level
¨
Data is unstructured
©
“flat” files
¨
High maintenance costs
©
data dependence; accessing data is difficult
©
ensuring data consistency and controlling access to data
¨
Sharing granularity is very coarse
¨
Difficulties in developing new applications
1-7
PROGRAM 1
PROGRAM 1
PROGRAM 2
Integrated
Database
DBMS
Query Processor
Transaction Mgr
…
Database Approach
1-8
What is a Database?

A database is an integrated and structured
collection of stored operational data used (shared)
by application systems of an enterprise
Manufacturing Product data
University Student data, courses
Hospital Patient data, facilities
Bank Account data
1-9
What is a Database?

A database (DB) is a structured collection of data
about the entities that exist in the environment that
is being modeled.

The structure of the database is determined by the
abstract data model that is used.

A database management system (DBMS) is the
generalized tool that facilitates the management of
and access to the database.
1-10
Data Model

Formalism that defines what the structure of the
data are

within a file

between files

File systems can at best specify data organization
within one file

Alternatives for business data

Hierarchical; network

Relational

Object-oriented

This structure is usually called the schema

A schema can have many instances
1-11
Example Relation Instances
ENO ENAME TITLE
E1 J. Doe Elect. Eng.
E2 M. Smith Syst. Anal.
E3 A. Lee Mech. Eng.
E4 J. Miller Programmer
E5 B. Casey Syst. Anal.
E6 L. Chu Elect. Eng.
E7 R. Davis Mech. Eng.
E8 J. Jones Syst. Anal.
EMP
ENO PNO RESP
E1 P1 Manager 12
DUR
E2 P1 Analyst 24
E2 P2 Analyst 6
E3 P3 Consultant 10
E3 P4 Engineer 48
E4 P2 Programmer 18
E5 P2 Manager 24
E6 P4 Manager 48
E7 P3 Engineer 36
E8 P3 Manager 40
WORKS
E7 P5 Engineer 23
PROJ
PNO PNAME BUDGET
P1 Instrumentation 150000
P3 CAD/CAM 250000
P2 Database Develop. 135000
P4 Maintenance 310000
P5 CAD/CAM 500000
1-12

Data constitute an organizational asset  Integrated
control

Reduction of redundancy

Avoidance of inconsistency

Sharability

Standards

Improved security

Data integrity

Programmer productivity  Data Independence
Why Database Technology
1-13

Programmer productivity

High data independence
Why Database Technology
Time
Maintenance
New system
development
TotalSystemCost
1-14

Invisibility (transparency) of the details of
conceptual organization, storage structure and
access strategy to the users

Logical

transparency of the conceptual organization

transparency of logical access strategy

Physical

transparency of the physical storage organization

transparency of physical access paths
Data Independence
1-15
ANSI/SPARC Architecture
External
Schema
Conceptual
Schema
Internal
Schema
Internal
view
Conceptual
view
External
view
External
view
External
view
Users
DBMS
EMP(ENO: string, ENAME: string, TITLE: string)
PROJ(PNO: string, PNAME: string, BUDGET: integer)
WORKS(ENO: string, PNO: string, RESP: string,
DUR: integer)
Store all the relations as unsorted files.
Build indexes on EMP(ENO), PROJ(PNO) and
WORKS(ENO,PNO).
ASSIGNMENT(ENO,PNO,ENAME,PNAME)
1-16
Database Functionality
Integrated schema
!
Users have uniform view of data
!
They see things only as relations (tables) in the
relational model
Declarative integrity and consistency enforcement
!
24000 ≤ Salary ≤ 250000
!
No employee can have a salary greater than his/her
manager.
!
User specifies and system enforces.
Individualized views
!
Restrictions to certain relations
!
Reorganization of relations for certain classes of users
1-17
Database Functionality (cont’d)

Declarative access
#
Query language - SQL
$
Find the names of all electrical engineers.
SELECT ENAME
FROM EMP
WHERE TITLE = “Elect. Eng.”
$
Find the names of all employees who have worked on a project
as a manager for more than 12 months.
SELECT EMP.ENAME
FROM EMP,ASG
WHERE RESP = “Manager”
AND DUR  12
AND EMP.ENO = ASG.ENO

System determined execution
#
Query processor  optimizer
1-18
Database Functionality (cont’d)

Transactions
#
Execute user requests as atomic units
#
May contain one query or multiple queries
#
Provide
$
Concurrency transparency
%
Multiple users may access the database, but they each see the
database as their own personal data
%
Concurrency control
$
Failure transparency
%
Even when system failure occurs, database consistency is not
violated
%
Logging and recovery
1-19
Database Functionality (cont’d)

Transaction Properties
'
Atomicity
(
All-or-nothing property
'
Consistency
(
Each transaction is correct and does not violate database
consistency
'
Isolation
(
Concurrent transactions do not interfere with each other
'
Durability
(
Once the transaction completes its work (commits), its effects
are guaranteed to be reflected in the database regardless of
what may occur
1-20
Application Programs
Operating System (?)
DBMS
App. development tools
Hardware
Place in a Computer System
1-21
System StructureNaïve users Application
programmers
Casual users Database
administrator
Forms
Application
Front ends DML Interface CLI DDL
Indexes System
Catalog
Data
files
DDL
Compiler
Disk Space Manager
Buffer Manager
File  Access Methods
Query Evaluation Engine
SQL Commands
RecoveryManager
Transaction

Lock
Manager
DBMS
1-22
Database Users
)
End user
0
Naïve or casual user
0
Accesses database either through forms or through application
front-ends
0
More sophisticated ones generate ad hoc queries using DML
)
Application programmer/developer
0
Designs and implements applications that access the database
(some may be used by end users)
)
Database administrator (DBA)
0
Defines and manages the conceptual schema
0
Defines application and user views
0
Monitors and tunes DBMS performance (defines/modifies internal
schema)
0
Loads and reformats the database
0
Responsible for security and reliability
1-23
DBMS Languages
1
Data Definition Language (DDL)
2
Defines conceptual schema, external schema, and internal schema,
as well as mappings between them
2
Language used for each level may be different
2
The definitions and the generated information is stored in system
catalog
1
Data Manipulation Language (DML)
2
Can be
3
embedded query language in a host language
3
“stand-alone” query language
2
Can be
3
Procedural: specify where and how (navigational)
3
Declarative: specify what
1-24
Brief History of Databases
4
1960s:
5
Early 1960s: Charles Bachmann developed first DBMS at
Honeywell (IDS)
6
Network model where data relationships are represented as a
graph.
5
Late 1960s: First commercially successful DBMS
developed at IBM (IMS)
6
Hierarchical model where data relationships are represented as a
tree
6
Still in use today (SABRE reservations; Travelocity)
5
Late 1960s: Conference On DAta Systems Languages
(CODASYL) model defined. This is the network model,
but more standardized.
1-25
Brief History of Databases
7
1970s:
8
1970: Ted Codd defined the relational data model at
IBM San Jose Laboratory (now IBM Almaden)
8
Two major projects start (both were operational in late
1970s)
9
INGRES at University of California, Berkeley
@
Became commercial INGRES, followed-up by POSTGRES
which was incorporated into Informix
9
System R at IBM San Jose Laboratory
@
Became DB2
8
1976: Peter Chen defined the Entity-Relationship (ER)
model
1-26
Brief History of Databases
7
1980s
8
Maturation of relational database technology
8
SQL standardization (mid-to-late 1980s) through ISO
8
The real growth period
7
1990s
8
Continued expansion of relational technology and
improvement of performance
8
Distribution becomes a reality
8
New data models: object-oriented, deductive
8
Late 1990s: incorporation of object-orientation in
relational DBMSs → Object-Relational DBMSs
8
New application areas: Data warehousing and OLAP,
Web and Internet, interest in text and multimedia

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  • 1. 1-1 What is “Data”?   ANSI definition: ¡ Data ¢ A representation of facts, concepts, or instructions in a formalized manner suitable for communication, interpretation, or processing by humans or by automatic means. £ Any representation such as characters or analog quantities to which meaning is or might be assigned. Generally, we perform operations on data or data items to supply some information about an entity.   Volatile vs. persistent data ¡ Our concern is primarily with persistent data 1-2 Early Data Management - Ancient History¤ Data are not stored on disk ¤ Programmer defines both logical data structure and physical structure (storage structure, access methods, I/O modes, etc) ¤ One data set per program. High data redundancy. PROGRAM 2 Data Management PROGRAM 3 Data Management PROGRAM 1 Data Management DATA SET 1 DATA SET 2 DATA SET 3
  • 2. 1-3 Problems ¥ There is no persistence. ¦ All data is transient and disappears when the program terminates. ¥ Random access memory (RAM) is expensive and limited ¦ All data may not fit available memory ¥ Programmer productivity low ¦ The programmer has to do a lot of tedious work. 1-4 File Processing - Recent (and Current) History§ Data are stored in files with interface between programs and files. § Various access methods exist (e.g., sequential, indexed, random) § One file corresponds to one or several programs. PROGRAM 1 Data Management FILE 1 FILE 2 RedundantData PROGRAM 2 Data Management PROGRAM 3 Data Management File System Services
  • 3. 1-5 File System Functions ¨ Mapping between logical files and physical files © Logical files: a file viewed by users and programs. Data may be viewed as a collection of bytes or as a collection of records (collection of bytes with a particular structure) Programs manipulate logical files © Physical files: a file as it actually exists on a storage device. Data usually viewed as a collection of bytes located at a physical address on the device Operating systems manipulate physical files. ¨ A set of services and an interface (usually called application independent interface – API) 1-6 Problems With File Systems ¨ Data are highly redundant © sharing limited and at the file level ¨ Data is unstructured © “flat” files ¨ High maintenance costs © data dependence; accessing data is difficult © ensuring data consistency and controlling access to data ¨ Sharing granularity is very coarse ¨ Difficulties in developing new applications
  • 4. 1-7 PROGRAM 1 PROGRAM 1 PROGRAM 2 Integrated Database DBMS Query Processor Transaction Mgr … Database Approach 1-8 What is a Database? A database is an integrated and structured collection of stored operational data used (shared) by application systems of an enterprise Manufacturing Product data University Student data, courses Hospital Patient data, facilities Bank Account data
  • 5. 1-9 What is a Database? A database (DB) is a structured collection of data about the entities that exist in the environment that is being modeled. The structure of the database is determined by the abstract data model that is used. A database management system (DBMS) is the generalized tool that facilitates the management of and access to the database. 1-10 Data Model Formalism that defines what the structure of the data are within a file between files File systems can at best specify data organization within one file Alternatives for business data Hierarchical; network Relational Object-oriented This structure is usually called the schema A schema can have many instances
  • 6. 1-11 Example Relation Instances ENO ENAME TITLE E1 J. Doe Elect. Eng. E2 M. Smith Syst. Anal. E3 A. Lee Mech. Eng. E4 J. Miller Programmer E5 B. Casey Syst. Anal. E6 L. Chu Elect. Eng. E7 R. Davis Mech. Eng. E8 J. Jones Syst. Anal. EMP ENO PNO RESP E1 P1 Manager 12 DUR E2 P1 Analyst 24 E2 P2 Analyst 6 E3 P3 Consultant 10 E3 P4 Engineer 48 E4 P2 Programmer 18 E5 P2 Manager 24 E6 P4 Manager 48 E7 P3 Engineer 36 E8 P3 Manager 40 WORKS E7 P5 Engineer 23 PROJ PNO PNAME BUDGET P1 Instrumentation 150000 P3 CAD/CAM 250000 P2 Database Develop. 135000 P4 Maintenance 310000 P5 CAD/CAM 500000 1-12 Data constitute an organizational asset Integrated control Reduction of redundancy Avoidance of inconsistency Sharability Standards Improved security Data integrity Programmer productivity Data Independence Why Database Technology
  • 7. 1-13 Programmer productivity High data independence Why Database Technology Time Maintenance New system development TotalSystemCost 1-14 Invisibility (transparency) of the details of conceptual organization, storage structure and access strategy to the users Logical transparency of the conceptual organization transparency of logical access strategy Physical transparency of the physical storage organization transparency of physical access paths Data Independence
  • 8. 1-15 ANSI/SPARC Architecture External Schema Conceptual Schema Internal Schema Internal view Conceptual view External view External view External view Users DBMS EMP(ENO: string, ENAME: string, TITLE: string) PROJ(PNO: string, PNAME: string, BUDGET: integer) WORKS(ENO: string, PNO: string, RESP: string, DUR: integer) Store all the relations as unsorted files. Build indexes on EMP(ENO), PROJ(PNO) and WORKS(ENO,PNO). ASSIGNMENT(ENO,PNO,ENAME,PNAME) 1-16 Database Functionality Integrated schema ! Users have uniform view of data ! They see things only as relations (tables) in the relational model Declarative integrity and consistency enforcement ! 24000 ≤ Salary ≤ 250000 ! No employee can have a salary greater than his/her manager. ! User specifies and system enforces. Individualized views ! Restrictions to certain relations ! Reorganization of relations for certain classes of users
  • 9. 1-17 Database Functionality (cont’d) Declarative access # Query language - SQL $ Find the names of all electrical engineers. SELECT ENAME FROM EMP WHERE TITLE = “Elect. Eng.” $ Find the names of all employees who have worked on a project as a manager for more than 12 months. SELECT EMP.ENAME FROM EMP,ASG WHERE RESP = “Manager” AND DUR 12 AND EMP.ENO = ASG.ENO System determined execution # Query processor optimizer 1-18 Database Functionality (cont’d) Transactions # Execute user requests as atomic units # May contain one query or multiple queries # Provide $ Concurrency transparency % Multiple users may access the database, but they each see the database as their own personal data % Concurrency control $ Failure transparency % Even when system failure occurs, database consistency is not violated % Logging and recovery
  • 10. 1-19 Database Functionality (cont’d) Transaction Properties ' Atomicity ( All-or-nothing property ' Consistency ( Each transaction is correct and does not violate database consistency ' Isolation ( Concurrent transactions do not interfere with each other ' Durability ( Once the transaction completes its work (commits), its effects are guaranteed to be reflected in the database regardless of what may occur 1-20 Application Programs Operating System (?) DBMS App. development tools Hardware Place in a Computer System
  • 11. 1-21 System StructureNaïve users Application programmers Casual users Database administrator Forms Application Front ends DML Interface CLI DDL Indexes System Catalog Data files DDL Compiler Disk Space Manager Buffer Manager File Access Methods Query Evaluation Engine SQL Commands RecoveryManager Transaction Lock Manager DBMS 1-22 Database Users ) End user 0 Naïve or casual user 0 Accesses database either through forms or through application front-ends 0 More sophisticated ones generate ad hoc queries using DML ) Application programmer/developer 0 Designs and implements applications that access the database (some may be used by end users) ) Database administrator (DBA) 0 Defines and manages the conceptual schema 0 Defines application and user views 0 Monitors and tunes DBMS performance (defines/modifies internal schema) 0 Loads and reformats the database 0 Responsible for security and reliability
  • 12. 1-23 DBMS Languages 1 Data Definition Language (DDL) 2 Defines conceptual schema, external schema, and internal schema, as well as mappings between them 2 Language used for each level may be different 2 The definitions and the generated information is stored in system catalog 1 Data Manipulation Language (DML) 2 Can be 3 embedded query language in a host language 3 “stand-alone” query language 2 Can be 3 Procedural: specify where and how (navigational) 3 Declarative: specify what 1-24 Brief History of Databases 4 1960s: 5 Early 1960s: Charles Bachmann developed first DBMS at Honeywell (IDS) 6 Network model where data relationships are represented as a graph. 5 Late 1960s: First commercially successful DBMS developed at IBM (IMS) 6 Hierarchical model where data relationships are represented as a tree 6 Still in use today (SABRE reservations; Travelocity) 5 Late 1960s: Conference On DAta Systems Languages (CODASYL) model defined. This is the network model, but more standardized.
  • 13. 1-25 Brief History of Databases 7 1970s: 8 1970: Ted Codd defined the relational data model at IBM San Jose Laboratory (now IBM Almaden) 8 Two major projects start (both were operational in late 1970s) 9 INGRES at University of California, Berkeley @ Became commercial INGRES, followed-up by POSTGRES which was incorporated into Informix 9 System R at IBM San Jose Laboratory @ Became DB2 8 1976: Peter Chen defined the Entity-Relationship (ER) model 1-26 Brief History of Databases 7 1980s 8 Maturation of relational database technology 8 SQL standardization (mid-to-late 1980s) through ISO 8 The real growth period 7 1990s 8 Continued expansion of relational technology and improvement of performance 8 Distribution becomes a reality 8 New data models: object-oriented, deductive 8 Late 1990s: incorporation of object-orientation in relational DBMSs → Object-Relational DBMSs 8 New application areas: Data warehousing and OLAP, Web and Internet, interest in text and multimedia