1. A View over Distributed databases
Vinod Bobba
Illinois State university
Billy Lim
ITK 478
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2. Agenda Introduction Point of view Conclusion
Distributed over Centralized
Fragmentation
Distributed Concurrency Control
Conclusion
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3. Distributed databases
Defining a global database as though it were centralized
Distributing portions of it at a variety of interconnected sites
Types
Homogeneous
Heterogeneous
Gateway protocols
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4. Distributed over centralized
Reflects organizational structure
No single point failure
Performance
Modifications are easy
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5. Data Replication Disadvantages
Reliability and Fast response
May avoid complicated distributed transaction integrity routines
De-couples nodes
Disadvantages
Additional requirements for storage space.
Additional time for update operations.
Integrity exposure of getting incorrect data if replicated data is not updated simultaneously.
Therefore, better when used for non-volatile data.
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6. Fragmentation Importance Horizontal Fragmentation
Breaking relations
Horizontal Fragmentation
Vertical Fragmentation
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7. Fragmentation Allocating Fragments Minimize cost of transmission
Redundant
Nonredundant
Minimize cost of transmission
Query type
Linier Integer Formulation
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8. Distributed Concurrency Control
Transactions
Transaction manager
Lock Management
Centralized
Primary Copy
Fully Distributed
Deadlock detection- wait for
Phantom Deadlocks
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9. Distributed Concurrency Control
Distributed Recovery
Abort Transactions
Commit protocols
Two phase commit
Coordinates activities at different sites involved in the transaction
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10. Better Performance Exploit Parallelism Commercial Systems
Interquery
Intraquery
Commercial Systems
Concurrency Control and recovery protocols are required – Synchronization
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11. Problems Need Network Scaling Complex data New database technologies
Advanced replica control protocols
Advanced transaction model
Processing methods
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12. Pros Increased Reliability and availability Local control over data
Modular growth
Low communication cost
Faster response for certain queries
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13. Cons Processing overhead Data integrity exposure
Slower response for certain queries
Software cost and complexity
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14. Q&A
Invite Questions
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