Week 5 Lecture

1. Week 5 Lecture Distributed Database Management Systems Suggestions for using the Lecture Slides Samuel Conn, Asst Professor

2. In this lecture, you will learn: • What a distributed database management system (DDBMS) is and what its components are • How database implementation is affected by different levels of data and process distribution • How transactions are managed in a distributed database environment • How database design is affected by the distributed database environment 2

3. Evolution of DDBMS • Decentralized database management systems (DDBMS) • Interconnected computer systems • Data/processing functions reside on multiple sites • 1970’s: Centralized DBMS • 1980’s: Social and Technical Changes • Ad hoc capability required • Decentralized management structure common • 1990’s: New forces • Internet and the World Wide Web used for data access and distribution • Data analysis through data mining and data warehousing 3

4. DDBMS Advantages • Data located near site with greatest demand • Faster data access • Faster data processing • Growth facilitation • Improved communications • Reduced operating costs • User-friendly interface • Less danger of single-point failure • Processor independence 4

5. DDBMS Disadvantages • Complexity of management and control • Security • Lack of standards • Increased storage requirements • Greater difficulty in managing data environment • Increased training costs 5

6. Distributed Processing Shares database’s logical processing among physically, networked independent sites Figure 10.1 6

7. Distributed Database Stores logically related database over physically independent sites Figure 10.2 7

8. Distributed Database vs. Distributed Processing • Distributed processing • Does not require distributed database • May be based on a single database on single computer • Copies or parts of database processing functions must be distributed to all data storage sites • Distributed database • Requires distributed processing • Both • Require a network to connect components 8

9. Functions of DDBMS • Application/end user interface • Validation to analyze data requests • Transformation to determine request components • Query optimization to find the best access strategy • Mapping to determine the data location • I/O interface to read or write data • Formatting to prepare the data for presentation • Security to provide data privacy • Backup and recovery • DB Administration • Concurrency Control • Transaction Management 9

10. Centralized Database Figure 10.3 10

11. Fully Distributed Database Management System Figure 10.4 11

12. DDBMS Components • Computer workstations • Network hardware and software components • Communications media • Transaction processor (TP) • Also called application manager (AP) or transaction manager (TM) • Data processor (DP) • Also called data manager (DM) 12

13. Distributed Database Components Figure 10.5 13

14. DDBMS Protocols • Interface with network to transport data and commands between DPs and TPs • Synchronize data received from DPs and route to appropriate TPs • Ensure common database functions • Security • Concurrency control • Backup and recovery 14

15. Levels of Data and Process Distribution Database systems can be classified based on process distribution and data distribution Table 10.1 15

16. Single-Site Processing, Single-Site Data (SPSD) • All processing on single CPU or host computer • All data are stored on host computer disk • DBMS located on the host computer • DBMS accessed by dumb terminals • Typical of mainframe and minicomputer DBMSs • Typical of 1st generation of single-user microcomputer database 16

17. Single-Site Processing, Single-Site Data (con’t.) Figure 10.6 17

18. Multiple-Site Processing, Single-Site Data (MPSD) • Requires network file server • Applications accessed through LAN • Variation known as client/server architecture Figure 10.7 18

19. Multiple-Site Processing, Multiple-Site Data (MPMD) • Fully distributed DDBMS with support for multiple DPs and TPs at multiple sites • Homogeneous I • Integrate one type of centralized DBMS over the network • Heterogeneous • Integrate different types of centralized DBMSs over a network 19

20. Heterogeneous Distributed Database Scenario Figure 10.8 20

21. Distributed DB Transparency • Allows end users to feel like only database user • Hides complexities of distributed database • Transparency features • Distribution • Transaction • Failure • Performance • Heterogeneity 21

22. Distribution Transparency • Allows management of a physically dispersed database as though it were centralized • Three Levels • Fragmentation transparency • Location transparency • Local mapping transparency Table 10.2 22

23. Transaction Transparency • Ensures transactions maintain integrity and consistency • Completed only if all involved database sites complete their part of the transaction • Management mechanisms • Remote request • Remote transaction • Distributed transaction • Distributed request 23

24. Remote Request Figure 10.10 24

25. Remote Transaction Figure 10.11 25

26. Distributed Transaction Figure 10.12 26

27. Distributed Requests Figure 10.13 27

28. Distributed Requests (con’t.) Figure 10.14 28

29. Distributed Concurrency Control • Multi-site, multiple-process operations more likely to create data inconsistencies and deadlocked transactions • Problems • Transaction committed by local DP • One DP could not commit transaction’s result • Yields inconsistent database 29

30. Two-Phase Commit Protocol • DO-UNDO-REDO protocol • Write-ahead protocol • Two kinds of nodes • Coordinator • Subordinates • Phases • Preparation • Coordinator sends message to all subordinates • Confirms all are ready to commit or abort • Final Commit • Ensures all subordinates have committed or aborted 30

31. Performance Transparency and Query Optimization • Objective: Minimize total cost associated with execution of request • Main costs • Access time • Communication • CPU time • Basis for query optimization algorithms • Optimum execution order • Sites accessed to minimize communication costs • Dynamic or static optimization • Statistically based vs. rule-based query optimization algorithms 31

32. Distributed Database Design • Partition database into fragments • Horizontal • Vertical • Mixed • Fragments to replicate • Storage of data copies at multiple sites • Fully, partially, un-replicated databases • Data allocation • Where to locate data • Centralized, partitioned, replicated 32

33. Client/Server Advantages Over DDBMS • Client/server less expensive • Client/server solutions allow use of microcomputer’s GUI • More people with PC skills than mainframe skills • PC is well established in workplace • Numerous data analysis and query tools exist • Considerable cost advantages to off-loading application development 33

34. Client/Server Disadvantages • Creates more complex environment with different platforms Increased number of users and sites creates security problems Training issues become more complex and expensive 34

35. Date’s 12 Commandments for Distributed Databases 1. Local Site Independence 2. Central Site Independence 3. Failure Independence 4. Location Transparency 5. Fragmentation Transparency 6. Replication Transparency 35

36. Date’s 12 Commandments for Distributed Databases 7. Distributed Query Processing 8. Distributed Transaction Processing 9. Hardware Independence 10. Operating System Independence 11. Network Independence 12. Database Independence 36