1. Databases
Alan Medlar
amedlar@cs.ucl.ac.uk

2. Schedule
• Today: Introduction
• Monday 2 Feb: Networking
nd
• Monday 2 Feb: Principles of Transactions
nd
• Tuesday 3 Feb: Concurrent Transactions
rd
• To be decided: Distributed Transactions

3. Introduction

4. Introduction
• Why do we care about databases?

5. Introduction
• Why do we care about databases?
• Abstraction

6. Introduction
• Why do we care about databases?
• Abstraction
• Details of storage and access are irrelevant

7. Introduction
• Why do we care about databases?
• Abstraction
• Details of storage and access are irrelevant
• Concurrency

8. Introduction
• Why do we care about databases?
• Abstraction
• Details of storage and access are irrelevant
• Concurrency
• Crash recovery

9. Introduction
• Why do we care about databases?
• Abstraction
• Details of storage and access are irrelevant
• Concurrency
• Crash recovery
• Integrity and Security (privacy)

10. Introduction
• Why do we care about databases?
• Abstraction
• Details of storage and access are irrelevant
• Concurrency
• Crash recovery
• Integrity and Security (privacy)
• Multi-user

11. Centralised Databases

12. Centralised Databases
Bottleneck!
Communication
overhead!
Single point
of failure!

13. Centralised Databases
• Bad news...
• Performance
• Processing
• I/O
• Distributed nature of data (departments,
companies, “mashups”)
• Availability (single point of failure)

14. Distributed Databases

15. Distributed Databases
Distributed
Processing
Distributed
{
Storage
Localised
Traffic

16. Distributed Databases
• Definition: A single DBMS running across
multiple CPUs, disks and/or networks,
designed to permit safe parallel access.

17. Concepts
• Distributed Processing
• Central database, distributed processing

18. Distributed Processing
• Multiple processors or cores
• Same memory (multi-core)
• Same disk (networked storage)
• Concurrency Control provided by
transactions

19. Concepts
• Distributed Processing
• Central database, distributed processing
• Ad-hoc Distributed Database
• Database physically distributed over
network

20. Distributed Databases
• Fragmentation
• Large dataset broken up into smaller components

21. Distributed Databases
• Fragmentation
• Large dataset broken up into smaller components
• Allocation
• Fragments should be stored according to usage

22. Distributed Databases
• Fragmentation
• Large dataset broken up into smaller components
• Allocation
• Fragments should be stored according to usage
• Replication
• Copy maintained at multiple sites to take
advantage of additional processing power or
decreased latency

23. Distributed Databases
• Might be implicit!
Fragmentation
• Large dataset broken up into smaller components
• Allocation
• Fragments should be stored according to usage
• Replication
• Copy maintained at multiple sites to take
advantage of additional processing power or
decreased latency

24. Distributed Databases (2)
• How do we decide how to fragment a
database?
• Data, application and usage dependant!

25. Distributed Databases (2)
• How do we decide how to fragment a
database?
• Data, application and usage dependant!
• Goals:
• Locality
• Minimal Communication
• Balance storage, processing, monetary costs

26. Concepts
• Distributed Processing
• Central database, distributed processing
• Ad-hoc Distributed Database
• Database physically distributed over
network
• Distributed DBMS (DDBMS)
• Software that makes distribution transparent

27. Distributed DBMS
• Key Concept: Transparency

28. Distributed DBMS
• Key Concept: Transparency
• Transparent Distribution

29. Distributed DBMS
• Key Concept: Transparency
• Transparent Distribution
• One centralised database from
perspective of user (programmer)

30. Distributed DBMS
• Key Concept: Transparency
• Transparent Distribution
• One centralised database from
perspective of user (programmer)
• Transparent Transactions

31. Distributed DBMS
• Key Concept: Transparency
• Transparent Distribution
• One centralised database from
perspective of user (programmer)
• Transparent Transactions
• Integrity of data maintained across
multiple databases

32. Distributed DBMS (2)
• Requires advanced:
• Recovery Services
• Concurrency control
• Focus of this course

33. Summary
• Advantages

34. Summary
• Advantages
• Performance

35. Summary
• Advantages
• Performance
• Reflect organisational structure

36. Summary
• Advantages
• Performance
• Reflect organisational structure
• Economics

37. Summary
• Advantages
• Performance
• Reflect organisational structure
• Economics
• Modular Growth

38. Summary
• Advantages
• Performance
• Reflect organisational structure
• Economics
• Modular Growth
• Availability

39. Summary
• Advantages
• Performance
• Reflect organisational structure
• Economics
• Modular Growth
• Availability
• Reliability

40. Summary (2)
• Disadvantages

41. Summary (2)
• Disadvantages
• Complexity (design, transparency, integrity)

42. Summary (2)
• Disadvantages
• Complexity (design, transparency, integrity)
• Security more of an issue

43. Summary (2)
• Disadvantages
• Complexity (design, transparency, integrity)
• Security more of an issue
• Maintenance Costs

44. Summary (2)
• Disadvantages
• Complexity (design, transparency, integrity)
• Security more of an issue
• Maintenance Costs
• Lack of standards (so much dependant on
data, application, usage, etc)

45. Next: Transactions...