2011 Db Intro

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Tecnología

Databases
Alan Medlar

amedlar@cs.ucl.ac.uk

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

Introduction
• Why do we care about databases?

Introduction
• Why do we care about databases?

• Abstraction

Introduction
• Why do we care about databases?

• Abstraction

• Details of storage and access are irrelevant

Introduction
• Why do we care about databases?

• Abstraction

• Details of storage and access are irrelevant

• Concurrency

Introduction
• Why do we care about databases?

• Abstraction

• Details of storage and access are irrelevant

• Concurrency

• Crash recovery

Introduction
• Why do we care about databases?

• Abstraction

• Details of storage and access are irrelevant

• Concurrency

• Crash recovery

• Integrity and Security (privacy)

Centralised Databases

Bottleneck!

Communication
overhead!

Single point
of failure!

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

Distributed Databases
Distributed
Processing
Distributed

{
Storage

Localised
Trafﬁc

Distributed Databases

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

Concepts
• Distributed Processing

• Central database, distributed processing

Distributed Processing

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

Concepts
• Distributed Processing

• Central database, distributed processing

• Ad-hoc Distributed Database

• Database physically distributed over
network

Distributed Databases
• Fragmentation

• Large dataset broken up into smaller components

Distributed Databases
• Fragmentation

• Large dataset broken up into smaller components

• Allocation

• Fragments should be stored according to usage

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

Distributed Databases (2)
• How do we decide how to fragment a
database?

• Data, application and usage dependant!

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

Distributed DBMS
• Key Concept: Transparency

Distributed DBMS
• Key Concept: Transparency
• Transparent Distribution

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

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

Distributed DBMS (2)

• Requires advanced:
• Recovery Services
• Concurrency control
• Focus of this course

Summary
• Advantages

• Performance

• Reﬂect organisational structure

Summary
• Advantages

• Performance

• Reﬂect organisational structure

• Economics

Summary
• Advantages

• Performance

• Reﬂect organisational structure

• Economics

• Modular Growth

Summary
• Advantages

• Performance

• Reﬂect organisational structure

• Economics

• Modular Growth

• Availability

Summary
• Advantages

• Performance

• Reﬂect organisational structure

• Economics

• Modular Growth

• Availability

• Reliability

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

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

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

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)

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panagenda

2011 Db Intro

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...

2011 Db Intro

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