1. (C) 2000, The University of Michigan 1 Database Application Design Handout #8 February 25, 2000

2. (C) 2000, The University of Michigan 2 Course information Instructor: Dragomir R. Radev (radev@si.umich.edu) Office: 305A, West Hall Phone: (734) 615-5225 Office hours: Thursdays 3-4 and Fridays 1-2 Course page: http://www.si.umich.edu/~radev/654w00 Class meets on Fridays, 2:30 - 5:30 PM, 311 WH

3. (C) 2000, The University of Michigan 3 Managing multi-user databases (cont’d)

4. (C) 2000, The University of Michigan 4 Concurrency control Lax and strict policies Atomic transactions (LUWs = logical units of work) –Example: customer+salesperson Concurrent transaction processing: interlocking Lost update problem

5. (C) 2000, The University of Michigan 5 Example User A: –Read item 100 –Reduce by 5 –Write item 100 User B: –Read item 200 –Reduce by 3 –Write item 200

6. (C) 2000, The University of Michigan 6 Resource locking Locks: implicit, explicit Example: two users

7. (C) 2000, The University of Michigan 7 Example User A: –Lock item 100 –Read item 100 –Reduce by 5 –Write item 100 User B: –Lock item 100 –Read item 100 –Reduce by 3 –Write item 100

8. (C) 2000, The University of Michigan 8 Example (cont’d) 1. Lock item 100 for A 2. Read item 100 for A 3. Lock item 100 for B; cannot 4. Decrease 100 by 5 5. Write item 100 for A 6. Release A’s lock on 100 7. Lock item 100 for B 8. Read item 100 for B 9. Decrease item 100 by 3 10. Write 100 for B 11. Release B’s lock on 100

9. (C) 2000, The University of Michigan 9 Resource locking Serizalizable transaction –2PL: growing phase, followed by a shrinking phase COMMIT and ROLLBACK DEADLOCKS

10. (C) 2000, The University of Michigan 10 Transaction isolation levels Exclusive use Repeatable read: mix of shared and exclusive locks Dirty read: for reports which don’t necessarily need to contain the latest data

11. (C) 2000, The University of Michigan 11 Cursor types Forward only: changes made to earlier records are hidden Static: any changes are hidden Dynamic: all changes are visible

12. (C) 2000, The University of Michigan 12 Database recovery Reprocessing: uses database saves Rollback/Rollforward : uses transaction logs, before-images, and after-images

13. (C) 2000, The University of Michigan 13 Database security Users, groups, permissions, objects Permissions: –CONNECT: ALTER SESSION, CREATE TABLE, CREATE VIEW

14. (C) 2000, The University of Michigan 14 Application security Usually done on the Web server ASP script modifies SQL statement: SELECT * FROM EMPLOYEE

15. (C) 2000, The University of Michigan 15 Sharing enterprise data

16. (C) 2000, The University of Michigan 16 Enterprise DB architectures Teleprocessing systems Client-server systems File-sharing systems Distributed database systems: vertical and horizontal fragmentation

17. (C) 2000, The University of Michigan 17 Comparing distributed DB architectures Unified database Distributed databases Single Nonpartitioned Nonreplicated Partitioned Nonreplicated Nonpartitioned Replicated Partitioned Replicated Increased security risk Increased difficulty of control Increased cost/complexity Increased availability Increased flexibility Increased independence Increased parallelism + + + + + + + - - - - + + +

18. (C) 2000, The University of Michigan 18 Problems in downloaded databases Coordination Consistency Access control Computer crime

19. (C) 2000, The University of Michigan 19 On Line Analytic Processing (OLAP) Hypercubes, axes, dimensions, slices Values of a dimension are called members Levels: hierarchical organization: e.g., date, month, year CROSSJOIN ({Existing Structure, New Construction}, {California.Children, Nevada})

20. 20 OLAP SQL CREATE CUBE HousingSalesCube ( DIMENSION Time TYPE TIME, LEVEL Year TYPE YEAR, LEVEL Quarter TYPE QUARTER, LEVEL Month TYPE MONTH, DIMENSION Location, LEVEL USA TYPE ALL, LEVEL State, LEVEL City, DIMENSION HousingCategory, DIMENSION HousingType, MEASURE SalesPrice, FUNCTION AVG, MEASURE AskingPrice, FUNCTION AVG )

21. (C) 2000, The University of Michigan 21 KDD: Data Mining

22. (C) 2000, The University of Michigan 22 Association rules X  Y 65% of all customers who buy beer and tomato sauce also buy pasta and chicken wings Support (X) Confidence (X  Y) = Support(X+Y) / Support (X)

23. (C) 2000, The University of Michigan 23 Object-oriented data processing

24. (C) 2000, The University of Michigan 24 Introduction OOP objects: encapsulated structures with attributes and methods Interface + implementation Inheritance Polymorphism Transient and persistent objects

25. (C) 2000, The University of Michigan 25 Final project guidelines

26. 26 Checklist Introduction User interviews/needs: table, reports, queries, forms Initial data model ER model Decomposition SQL code Documentation Evaluation, Future work Schedule Sustainability Snapshots Presentation Demo

27. (C) 2000, The University of Michigan 27 Grading Project: 40% - design 10% - implementation 10% - documentation 10% - presentation+demo 10%

28. (C) 2000, The University of Michigan 28 Readings for next time Kroenke –Chapter 14: Sharing Enterprise Data –Chapter 17: Object-Oriented Database Processing YRK (optional) –Chapter 14: Java and JDBC