1. Distributed DBMSPage 4. 1© 1998 M. Tamer Özsu & Patrick Valduriez 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 o Parallel Database Systems o Distributed Object DBMS o Database Interoperability o Current Issues

2. Distributed DBMSPage 4. 2© 1998 M. Tamer Özsu & Patrick Valduriez  Defines the structure of the system  components identified  functions of each component defined  interrelationships and interactions between components defined Architecture

3. Distributed DBMSPage 4. 3© 1998 M. Tamer Özsu & Patrick Valduriez ANSI/SPARC Architecture External Schema Conceptual Schema Internal Schema Internal view Users External view Conceptual view External view External view

4. Distributed DBMSPage 4. 4© 1998 M. Tamer Özsu & Patrick Valduriez 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. Standardization

5. Distributed DBMSPage 4. 5© 1998 M. Tamer Özsu & Patrick Valduriez 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) } ] Conceptual Schema Definition

6. Distributed DBMSPage 4. 6© 1998 M. Tamer Özsu & Patrick Valduriez 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) } ] Conceptual Schema Definition

7. Distributed DBMSPage 4. 7© 1998 M. Tamer Özsu & Patrick Valduriez 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) } ] Internal Schema Definition

8. Distributed DBMSPage 4. 8© 1998 M. Tamer Özsu & Patrick Valduriez Create a BUDGET view from the PROJ relation CREATE VIEW BUDGET(PNAME, BUD) AS SELECT PNAME, BUDGET FROM PROJ External View Definition – Example 1

9. Distributed DBMSPage 4. 9© 1998 M. Tamer Özsu & Patrick Valduriez Create a Payroll view from relations EMP and TITLE_SALARY CREATEVIEW PAYROLL (ENO, ENAME, SAL) AS SELECT EMP.ENO,EMP.ENAME,PAY.SAL FROM EMP, PAY WHERE EMP.TITLE = PAY.TITLE External View Definition – Example 2

10. Distributed DBMSPage 4. 10© 1998 M. Tamer Özsu & Patrick Valduriez DBMS Implementation Alternatives Distribution Heterogeneity Autonomy Client/server Peer-to-peer Distributed DBMS Federated DBMS Distributed multi-DBMS Multi-DBMS

11. Distributed DBMSPage 4. 11© 1998 M. Tamer Özsu & Patrick Valduriez 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.

12. Distributed DBMSPage 4. 12© 1998 M. Tamer Özsu & Patrick Valduriez Datalogical Distributed DBMS Architecture... ES 1 ES 2 ES n GCS LCS 1 LCS 2 LCS n LIS 1 LIS 2 LIS n

13. Distributed DBMSPage 4. 13© 1998 M. Tamer Özsu & Patrick Valduriez Datalogical Multi-DBMS Architecture... GCS … … GES 1 LCS 2 LCS n … … LIS 2 LIS n LES 11 LES 1 n LES n 1 LES nm GES 2 GES n LIS 1 LCS 1

14. Distributed DBMSPage 4. 14© 1998 M. Tamer Özsu & Patrick Valduriez Timesharing Access to a Central Database Communications DBMS Services Network Terminals or PC terminal emulators Batch requests Response No data storage Host running all software Application Software Database

15. Distributed DBMSPage 4. 15© 1998 M. Tamer Özsu & Patrick Valduriez Multiple Clients/Single Server Communications Client Services Applications Communications DBMS Services LAN High-level requests Filtered data only Communications Client Services Applications Communications Client Services Applications Database

16. Distributed DBMSPage 4. 16© 1998 M. Tamer Özsu & Patrick Valduriez Task Distribution Application Communications Manager Lock Manager Storage Manager Page & Cache Manager Query Optimizer QL Interface Programmatic Interface … SQL query result table Database

17. Distributed DBMSPage 4. 17© 1998 M. Tamer Özsu & Patrick Valduriez 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

18. Distributed DBMSPage 4. 18© 1998 M. Tamer Özsu & Patrick Valduriez Problems With Multiple- Client/Single Server Server forms bottleneck Server forms single point of failure Database scaling difficult

19. Distributed DBMSPage 4. 19© 1998 M. Tamer Özsu & Patrick Valduriez Multiple Clients/Multiple Servers Communications Client Services Applications LAN directory caching query decomposition commit protocols Communications DBMS Services Database Communications DBMS Services Database

20. Distributed DBMSPage 4. 20© 1998 M. Tamer Özsu & Patrick Valduriez Server-to-Server Communications DBMS Services LAN Communications DBMS Services SQL interface programmatic interface other application support environments Communications Client Services Applications Database

21. Distributed DBMSPage 4. 21© 1998 M. Tamer Özsu & Patrick Valduriez Peer-to-Peer Component Architecture Database DATA PROCESSORUSER PROCESSOR USER User requests System responses External Schema User Interface Handler Global Conceptual Schema Semantic Data Controller Global Execution Monitor System Log Local Recovery Manager Local Internal Schema Runtime Support Processor Local Query Processor Local Conceptual Schema Global Query Optimizer GD/D

22. Distributed DBMSPage 4. 22© 1998 M. Tamer Özsu & Patrick Valduriez Components of a Multi-DBMS Global Requests Responses … DBMSDBMS User Interface Query Processor Query Optimizer Transaction Manager Scheduler Recovery Manager Runtime Sup. Processor USER GTPGQP GQOGSGRM GUI Local Requests Component Interface Processor (CIP) DBMSDBMS User Interface Query Processor Query Optimizer Transaction Manager Scheduler Recovery Manager Runtime Sup. Processor Local Requests Component Interface Processor (CIP)

23. Distributed DBMSPage 4. 23© 1998 M. Tamer Özsu & Patrick Valduriez Directory Issues Type Location Replication Global & central & non-replicated Local & central & non-replicated (?) Global & distributed & non-replicated (?) Local & distributed & non-replicated Global & central & replicated (?) Global & distributed & replicated Local & distributed & replicated Local & central & replicated (?)