Distributed Databases

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Distributed Databases
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Learning Objectives

• What a distributed database management system
  (DDBMS) is and what its components are
• How database implementation is affected by
  different levels of data and process distribution
• How transactions are managed in a distributed
  database environment
• How database design is affected by the
  distributed database environment

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DDBMS

• Decentralized database management systems (DDBMS)
  Distributed Databases are logically related
  data over interconnected computer systems in
  which both data and processing functions reside
  on multiple sites.

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Evolution of DDBMS

• Decentralized database management systems (DDBMS)
  
• Interconnected computer systems
• Data/processing functions reside on multiple
  sites
• 1970s Centralized DBMS
• 1980s Social and Technical Changes
• Ad hoc capability required
• Decentralized management structure common
• 1990s New forces
• Internet and the World Wide Web used for data
  access and distribution
• Data analysis through data mining and data
  warehousing

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DDBMS Advantages

• Data located near site with greatest demand
• Faster data access
• Faster data processing
• Growth facilitation
• Improved communications
• Reduced operating costs
• User-friendly interface
• Less danger of single-point failure
• Processor independence

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DDBMS Disadvantages

• Complexity of management and control
• Security
• Lack of standards
• Increased storage requirements
• Greater difficulty in managing data environment
• Increased training costs

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Distributed Processing

• Shares databases logical processing among
  physically, networked independent sites

Figure 10.1
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Distributed Database

• Stores logically related database over
  physically independent sites

Figure 10.2
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Distributed Database vs. Distributed Processing

• Distributed processing
• Does not require distributed database
• May be based on a single database on single
  computer
• Copies or parts of database processing functions
  must be distributed to all data storage sites
• Distributed database
• Requires distributed processing
• Both
• Require a network to connect components

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Functions of DDBMS

• Application/end user interface
• Validation to analyze data requests
• Transformation to determine request components
• Query optimization to find the best access
  strategy
• Mapping to determine the data location
• I/O interface to read or write data
• Formatting to prepare the data for presentation
• Security to provide data privacy
• Backup and recovery
• DB Administration
• Concurrency Control
• Transaction Management

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Centralized Database
Figure 10.3
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Fully Distributed Database Management System
Figure 10.4
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DDBMS Components

• Computer workstations
• Network hardware and software components
• Communications media
• Transaction processor (TP)
• Also called application manager (AP) or
  transaction manager (TM)
• Data processor (DP)
• Also called data manager (DM)

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Distributed Database Components
Figure 10.5
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DDBMS Protocols

• Interface with network to transport data and
  commands between DPs and TPs
• Synchronize data received from DPs and route to
  appropriate TPs
• Ensure common database functions
• Security
• Concurrency control
• Backup and recovery

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Levels of Data and Process Distribution

• Database systems can be classified based on
  process distribution and data distribution

Table 10.1
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Single-Site Processing, Single-Site Data (SPSD)

• All processing on single CPU or host computer
• All data are stored on host computer disk
• DBMS located on the host computer
• DBMS accessed by dumb terminals
• Typical of mainframe and minicomputer DBMSs
• Typical of 1st generation of single-user
  microcomputer database

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Single-Site Processing, Single-Site Data (cont.)
Figure 10.6
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Multiple-Site Processing, Single-Site Data (MPSD)

• Requires network file server
• Applications accessed through LAN
• Variation known as client/server architecture

Figure 10.7
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Multiple-Site Processing, Multiple-Site Data
(MPMD)

• Fully distributed DDBMS with support for multiple
  DPs and TPs at multiple sites
• Homogeneous I
• Integrate one type of centralized DBMS over the
  network
• Heterogeneous
• Integrate different types of centralized DBMSs
  over a network

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Heterogeneous Distributed Database Scenario
Figure 10.8
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Distributed DB Transparency

• Allows end users to feel like only database user
• Hides complexities of distributed database
• Transparency features
• Distribution
• Transaction
• Failure
• Performance
• Heterogeneity

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Distribution Transparency

• Allows management of a physically dispersed
  database as though it were centralized
• Three Levels
• Fragmentation transparency
• Location transparency
• Local mapping transparency

Table 10.2
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Transaction Transparency

• Ensures transactions maintain integrity and
  consistency
• Completed only if all involved database sites
  complete their part of the transaction
• Management mechanisms
• Remote request
• Remote transaction
• Distributed transaction
• Distributed request

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Remote Request
Figure 10.10
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Remote Transaction
Figure 10.11
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Distributed Transaction
Figure 10.12
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Distributed Requests
Figure 10.13
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Distributed Requests (cont.)
Figure 10.14
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Distributed Concurrency Control

• Multisite, multiple-process operations more
  likely to create data inconsistencies and
  deadlocked transactions
• Problems
• Transaction committed by local DP
• One DP could not commit transactions result
• Yields inconsistent database

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Two-Phase Commit Protocol

• DO-UNDO-REDO protocol
• Write-ahead protocol
• Two kinds of nodes
• Coordinator
• Subordinates
• Phases
• Preparation
• Coordinator sends message to all subordinates
• Confirms all are ready to commit or abort
• Final Commit
• Ensures all subordinates have committed or aborted

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Performance Transparency and Query Optimization

• Objective Minimize total cost associated with
  execution of request
• Main costs
• Access time
• Communication
• CPU time
• Basis for query optimization algorithms
• Optimum execution order
• Sites accessed to minimize communication costs
• Dynamic or static optimization
• Statistically based vs. rule-based query
  optimization algorithms

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Distributed Database Design

• Partition database into fragments
• Horizontal
• Vertical
• Mixed
• Fragments to replicate
• Storage of data copies at multiple sites
• Fully, partially, unreplicated databases
• Data allocation
• Where to locate data
• Centralized, partitioned, replicated

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Client/Server Advantages Over DDBMS

• Client/server less expensive
• Client/server solutions allow use of
  microcomputers GUI
• More people with PC skills than mainframe skills
• PC is well established in workplace
• Numerous data analysis and query tools exist
• Considerable cost advantages to off-loading
  application development

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Client/Server Disadvantages

• Creates more complex environment with different
  platforms
• Increased number of users and sites creates
  security problems
• Training issues become more complex and expensive

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Dates 12 Commandments for Distributed Databases

• 1. Local Site Independence
• 2. Central Site Independence
• 3. Failure Independence
• 4. Location Transparency
• 5. Fragmentation Transparency
• 6. Replication Transparency

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Dates 12 Commandments for Distributed Databases

• 7. Distributed Query Processing
• 8. Distributed Transaction Processing
• 9. Hardware Independence
• 10. Operating System Independence
• 11. Network Independence
• 12. Database Independence