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Parallel and distributed databases
R & G Chapter 22
What is a distributed database? Why distribute a database
Scalability and performance
Resilience to failures
Throughput^ Data size
X^ versus X
Why distribute a database
Data is already distributed
Or needs to be distributed
Data is in multiple systems
Why not distribute a database You must earn your complexity!
Communication needed
Must build a complex infrastructure
Unpredictable latencies must be masked
More types of failures
More components to fail
Network failuresCongestion, timeouts
More complex planning
Communication cost plus I/O cost
May have to deal with heterogeneity
Different types of systems
Different schemas, possibly incompatibleDifferent administrative domains
Types of distributed databases
The old days: mainframes
Definitely not distributed!
Client-server
User interaction Data processing Network
Parallel database Primary/secondary
X
Multidatabase How do they work?
What is shared?
How to distribute the data?
How to process the data?
How to update the data?
Query processing
Intra-operator parallelism
Inter-operator parallelism
Parallel scanning filter filter filter filter filter filter Result Sorting Sorting Parallel hash join Hash() Join
Semi-join Inter-operator parallelism Updating distributed data
Synchronous: read-any-write-all
Reads are fast
Updating distributed data
Synchronous: voting
Updating distributed data
Synchronous: voting
Writes tolerant to disconnection
Consistency of distributed data
Should provide ACID
