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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
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)
Introduction
•   Why do we care about databases?

    •   Abstraction

        •   Details of storage and access are irrelevant

        •   Concurrency

        •   Crash recovery

    •   Integrity and Security (privacy)

    •   Multi-user
Centralised Databases
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 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
•   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
•                                      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
Concepts
•   Distributed Processing

    •   Central database, distributed processing

•   Ad-hoc Distributed Database

    •   Database physically distributed over
        network

•   Distributed DBMS (DDBMS)

    •   Software that makes distribution transparent
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
• Key Concept: Transparency
 • Transparent Distribution
   • One centralised database from
      perspective of user (programmer)
 • Transparent Transactions
  • Integrity of data maintained across
      multiple databases
Distributed DBMS (2)

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

    •   Performance
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
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)
Next: Transactions...

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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
  • 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
  • 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)
  • 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)

Notas del editor