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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.
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.
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.
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.
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.
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.
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.
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.
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.
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
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
Datalogical Distributed
DBMS Architecture

                   ES1              ES2      ...      ESn




                                    GCS



                   LCS1            LCS2      ...     LCSn



                   LIS1             LIS2     ...      LISn




Distributed DBMS    © 1998 M. Tamer Özsu & Patrick Valduriez   Page 4. 1
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
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
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
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
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
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
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
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
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
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
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

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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
  • 12. Datalogical Distributed DBMS Architecture ES1 ES2 ... ESn GCS LCS1 LCS2 ... LCSn LIS1 LIS2 ... LISn 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