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RDBMS
- 1. Outline
Introduction
Background
Distributed DBMS Architecture
Datalogical Architecture
Implementation Alternatives
Component Architecture
Distributed DBMS Architecture
Distributed Database Design
Semantic Data Control
Distributed Query Processing
Distributed Transaction Management
Parallel Database Systems
Distributed Object DBMS
Database Interoperability
Current Issues
Distributed DBMS © 1998 M. Tamer Özsu & Patrick Valduriez Page 4.
- 2. Architecture
Defines the structure of the system
components identified
functions of each component defined
interrelationships and interactions between components
defined
Distributed DBMS © 1998 M. Tamer Özsu & Patrick Valduriez Page 4.
- 3. ANSI/SPARC Architecture
Users
External External External External
Schema view view view
Conceptual Conceptual
view
Schema
Internal Internal view
Schema
Distributed DBMS © 1998 M. Tamer Özsu & Patrick Valduriez Page 4.
- 4. Standardization
Reference Model
A conceptual framework whose purpose is to divide standardization
work into manageable pieces and to show at a general level how these
pieces are related to one another.
Approaches
Component-based
Components of the system are defined together with the
interrelationships between components.
Good for design and implementation of the system.
Function-based
Classes of users are identified together with the functionality that
the system will provide for each class.
The objectives of the system are clearly identified. But how do you
achieve these objectives?
Data-based
Identify the different types of describing data and specify the
functional units that will realize and/or use data according to these
views.
Distributed DBMS © 1998 M. Tamer Özsu & Patrick Valduriez Page 4.
- 5. Conceptual Schema Definition
RELATION EMP [
KEY = {ENO}
ATTRIBUTES = {
ENO : CHARACTER(9)
ENAME : CHARACTER(15)
TITLE : CHARACTER(10)
}
]
RELATION PAY [
KEY = {TITLE}
ATTRIBUTES = {
TITLE : CHARACTER(10)
SAL : NUMERIC(6)
}
]
Distributed DBMS © 1998 M. Tamer Özsu & Patrick Valduriez Page 4.
- 6. Conceptual Schema Definition
RELATION PROJ [
KEY = {PNO}
ATTRIBUTES = {
PNO : CHARACTER(7)
PNAME : CHARACTER(20)
BUDGET : NUMERIC(7)
}
]
RELATION ASG [
KEY = {ENO,PNO}
ATTRIBUTES = {
ENO : CHARACTER(9)
PNO : CHARACTER(7)
RESP : CHARACTER(10)
DUR : NUMERIC(3)
}
]
Distributed DBMS © 1998 M. Tamer Özsu & Patrick Valduriez Page 4.
- 7. Internal Schema Definition
RELATION EMP [
KEY = {ENO}
ATTRIBUTES = {
ENO : CHARACTER(9)
ENAME : CHARACTER(15)
TITLE : CHARACTER(10)
}
]
⇓
INTERNAL_REL EMPL [
INDEX ON E# CALL EMINX
FIELD = {
HEADER : BYTE(1)
E# : BYTE(9)
ENAME : BYTE(15)
TIT : BYTE(10)
}
]
Distributed DBMS © 1998 M. Tamer Özsu & Patrick Valduriez Page 4.
- 8. External View Definition –
Example 1
Create a BUDGET view from the PROJ relation
CREATE VIEW BUDGET(PNAME, BUD)
AS SELECT PNAME, BUDGET
FROM PROJ
Distributed DBMS © 1998 M. Tamer Özsu & Patrick Valduriez Page 4.
- 9. External View Definition –
Example 2
Create a Payroll view from relations EMP and
TITLE_SALARY
CREATE VIEW PAYROLL (ENO, ENAME, SAL)
AS SELECT EMP.ENO,EMP.ENAME,PAY.SAL
FROM EMP, PAY
WHERE EMP.TITLE = PAY.TITLE
Distributed DBMS © 1998 M. Tamer Özsu & Patrick Valduriez Page 4.
- 10. DBMS Implementation
Alternatives
Distribution
Distributed
Peer-to-peer
multi-DBMS
Distributed DBMS
Client/server
Autonomy
Multi-DBMS
Federated DBMS
Heterogeneity
Distributed DBMS © 1998 M. Tamer Özsu & Patrick Valduriez Page 4. 1
- 11. Dimensions of the Problem
Distribution
Whether the components of the system are located on the same
machine or not
Heterogeneity
Various levels (hardware, communications, operating system)
DBMS important one
data model, query language,transaction management
algorithms
Autonomy
Not well understood and most troublesome
Various versions
Design autonomy: Ability of a component DBMS to decide on
issues related to its own design.
Communication autonomy: Ability of a component DBMS to
decide whether and how to communicate with other DBMSs.
Execution autonomy: Ability of a component DBMS to execute
local operations in any manner it wants to.
Distributed DBMS © 1998 M. Tamer Özsu & Patrick Valduriez Page 4. 1
- 13. Datalogical Multi-DBMS
Architecture
GES1 GES2 ... GESn
LES11 … LES1n GCS LESn1 … LESnm
LCS1 LCS2 … LCSn
LIS1 LIS2 … LISn
Distributed DBMS © 1998 M. Tamer Özsu & Patrick Valduriez Page 4. 1
- 14. Timesharing Access to a Central
Database
Terminals or PC terminal emulators
• No data
storage
• Host
running all
software
Batch Response Network
requests
Communications
Application Software
DBMS Services
Database
Distributed DBMS © 1998 M. Tamer Özsu & Patrick Valduriez Page 4. 1
- 15. Multiple Clients/Single Server
Applications Applications Applications
Client Client Client
Services Services Services
Communications Communications Communications
LAN
High-level Filtered
requests data only
Communications
DBMS Services
Database
Distributed DBMS © 1998 M. Tamer Özsu & Patrick Valduriez Page 4. 1
- 16. Task Distribution
Application
QL Programmatic
Interface … Interface
Communications Manager
SQL result
query table
Communications Manager
Query Optimizer
Lock Manager
Storage Manager
Page & Cache Manager
Database
Distributed DBMS © 1998 M. Tamer Özsu & Patrick Valduriez Page 4. 1
- 17. Advantages of Client-Server
Architectures
More efficient division of labor
Horizontal and vertical scaling of resources
Better price/performance on client machines
Ability to use familiar tools on client machines
Client access to remote data (via standards)
Full DBMS functionality provided to client
workstations
Overall better system price/performance
Distributed DBMS © 1998 M. Tamer Özsu & Patrick Valduriez Page 4. 1
- 18. Problems With Multiple-
Client/Single Server
Server forms bottleneck
Server forms single point of failure
Database scaling difficult
Distributed DBMS © 1998 M. Tamer Özsu & Patrick Valduriez Page 4. 1
- 19. Multiple Clients/Multiple Servers
directory Applications
caching Client
query decomposition Services
Communications
commit protocols
LAN
Communications Communications
DBMS Services DBMS Services
Database Database
Distributed DBMS © 1998 M. Tamer Özsu & Patrick Valduriez Page 4. 1
- 20. Server-to-Server
SQL interface
Applications
programmatic
Client
interface Services
other application Communications
support
environments
LAN
Communications Communications
DBMS Services DBMS Services
Database Database
Distributed DBMS © 1998 M. Tamer Özsu & Patrick Valduriez Page 4. 2
- 21. Peer-to-Peer
Component Architecture
USER PROCESSOR DATA PROCESSOR
Global Local System Local
External Conceptual Conceptual Log Internal
Schema Schema GD/D Schema Schema
User
requests Database
Local Recovery
User Interface
Semantic Data
Global Query
Local Query
Controller
Execution
Optimizer
Processor
Processor
Handler
Manager
Runtime
Monitor
Support
USER Global
System
responses
Distributed DBMS © 1998 M. Tamer Özsu & Patrick Valduriez Page 4. 2
- 22. Components of a Multi-DBMS
USER
Global
Responses Requests
GTP GUI GQP
GS GRM GQO
Local Component Interface Processor Component Interface Processor Local
Request (CIP) (CIP) Request
s s
User Transaction Transaction User
D Interface Manager D Manager Interface
B Query
Scheduler B Scheduler
Query
M
Processor … M
Processor
Query Recovery Recovery Query
S Optimizer Manager S Manager Optimizer
Runtime Sup. Runtime Sup.
Processor Processor
Distributed DBMS © 1998 M. Tamer Özsu & Patrick Valduriez Page 4. 2
- 23. Directory Issues
Type
Local & central Local & distributed
Global & central & non-replicated (?) & non-replicated
& non-replicated
Global & distributed
Local & central & non-replicated (?)
& replicated (?)
Location
Global & central
& replicated (?)
Local & distributed
& replicated
Global & distributed
& replicated
Replication
Distributed DBMS © 1998 M. Tamer Özsu & Patrick Valduriez Page 4. 2