• Share
  • Email
  • Embed
  • Like
  • Save
  • Private Content
Lecture 08 distributed dbms
 

Lecture 08 distributed dbms

on

  • 8,552 views

 

Statistics

Views

Total Views
8,552
Views on SlideShare
8,547
Embed Views
5

Actions

Likes
1
Downloads
271
Comments
0

3 Embeds 5

http://pcte-mca-rdbms-harmeet-gill.blogspot.com 2
http://pcte-mca-rdbms-harmeet-gill.blogspot.in 2
http://www.pcte-mca-rdbms-harmeet-gill.blogspot.com 1

Accessibility

Categories

Upload Details

Uploaded via as Microsoft PowerPoint

Usage Rights

© All Rights Reserved

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Processing…
Post Comment
Edit your comment
  • 22
  • 22
  • 24
  • 26
  • 28
  • Product table should be Customer table and Customer table as Product table mistake in this slide

Lecture 08 distributed dbms Lecture 08 distributed dbms Presentation Transcript

  • Lecture 8 Distributed Database Management Systems
  • Different Types of Database System Contributed by: Isha Kushwah MCA-2008-11 Centralized database System
  • Content
    • What a distributed database management system (DDBMS)
    • DDBMS components
    • 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
  • Evolution of DDBMS
    • Decentralized database management systems (DDBMS)
      • Interconnected computer systems
      • Data/processing functions reside on multiple sites
    • 1970’s: Centralized DBMS
    • 1980’s: Social and Technical Changes
      • Ad hoc capability required
      • Decentralized management structure common
    • 1990’s: New forces
      • Internet and the World Wide Web used for data access and distribution
      • Data analysis through data mining and data warehousing
  • Problem in Centralized database Management
    • Performance degradation
    • High cost
    • Reliability problems
  • 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
  • DDBMS Disadvantages
    • Complexity of management and control
    • Security
    • Lack of standards
    • Increased storage requirements
    • Greater difficulty in managing data environment
    • Increased training costs
  • Distributed Processing
    • Shares database’s logical processing among physically, networked independent sites
    Figure 10.1
  • Distributed Database
    • Stores logically related database over physically independent sites
    Figure 10.2
  • 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
  • Functions of DDBMS
    • Application/end user interface
    • Validation
    • Transformation
    • Query optimization
    • Mapping
    • I/O interface
    • Formatting
    • Security
    • Backup and recovery
    • DB Administration
    • Concurrency Control
    • Transaction Management
  • 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
  • Centralized Database Figure 10.3
  • Fully Distributed Database Management System Figure 10.4
  • 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)
  • Distributed Database Components Figure 10.5
  • 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
  • Levels of Data and Process Distribution
    • Database systems can be classified based on process distribution and data distribution
    Table 10.1
  • 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
  • Single-Site Processing, Single-Site Data (con’t.) Figure 10.6
  • Multiple-Site Processing, Single-Site Data (MPSD)
      • Requires network file server
      • Applications accessed through LAN
      • Variation known as client/server architecture
    Figure 10.7
  • 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
  • Heterogeneous Distributed Database Scenario Figure 10.8
  • Distributed DB Transparency
    • Allows end users to feel like only database user
    • Hides complexities of distributed database
    • Transparency features
      • Distribution
      • Transaction
      • Failure
      • Performance
      • Heterogeneity
  • 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
  • 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
  • Remote Request Figure 10.10
  • Remote Transaction Figure 10.11
  • Distributed Transaction Figure 10.12
  • Distributed Requests Figure 10.13
  • Distributed Requests (con’t.) Figure 10.14
  • 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 transaction’s result
      • Yields inconsistent database
  • 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
  • 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
    • Automatic or Manual
    • Dynamic or static optimization
    • Statistically based vs. rule-based query optimization algorithms
  • 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
  • Client/Server Advantages Over DDBMS
    • Client/server less expensive
    • Client/server solutions allow use of microcomputer’s 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
  • 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
  • Date’s 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
  • Date’s 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