1. Introduction of Week 14 Return assignment 12-1
Collect assignment 3-1-6
Review of week 13
Transaction
Transaction log and audit trail
Concurrent control and potential problems
Lock method, deadlock, deadlock control
Optimistic method
Database backup and disaster recovery
Database Management Systems

2. Module 6 Advanced Database Concepts
Section 3: Distributed Database
Module 6 Advanced Database Concepts

3. Centralized DBMS
Database Management Systems

4. Distributed Database Environment
Database Management Systems

5. DDBMS Advantages Data are located near “greatest demand” site
Faster data access and data processing
Growth facilitation
Less danger of a single-point failure
Processor independence
Database Management Systems

6. DDBMS Disadvantages Complexity of management and control
Lack of standards
Increased storage requirements
Greater difficulty in managing the data environment
Increased training cost
Database Management Systems

7. Characteristics of Distributed Management Systems
Application interface
Data validation and transformation
Query optimization
Backup and recovery, DB administration
Concurrency control and transaction management
Must perform all the functions of a centralized DBMS
Must handle all necessary functions imposed by the distribution of data and processing
Must perform these additional functions transparently to the end user
Database Management Systems

8. A Fully Distributed Database Management System
Database Management Systems

9. Multiple-Site Data
Fully distributed database management system with support for multiple data processors and transaction processors at multiple sites
Homogeneous DDBMS - integrate only one type of centralized DBMS over a network
Heterogeneous DDBMS - integrate different types of DBMS that may even support different data models (relational or hierarchical) running under different computer systems over a network
Database Management Systems

10. Heterogeneous Distributed Database Scenario
Database Management Systems

11. Distributed Database Transparency Features
Distribution transparency
Transaction transparency
Failure transparency
Performance transparency
Heterogeneity transparency
Database Management Systems

12. 1. Distribution Transparency
Allows management of a physically dispersed database as though it were a centralized database
Three levels of distribution transparency are recognized:
Fragmentation transparency
Location transparency
Local mapping transparency
Database Management Systems

13. Fragment Locations
Database Management Systems

14. 2. Transaction Transparency
Ensures database transactions will maintain distributed database’s integrity and consistency
Database Management Systems

15. Distributed Transaction Request
Database Management Systems

16. Distributed Concurrency Control
Multi-site, multiple-process operations are much more likely to create data inconsistencies and deadlocked transactions than are single-site systems
Database Management Systems

17. Premature COMMIT
Database Management Systems

18. Two-Phase Commit Protocol
Final COMMIT must not be issued until all sites have committed their parts of the transaction
Two-phase commit protocol requires each individual DP’s transaction log entry be written before the database fragment is actually updated
Database Management Systems

19. Two - Phase Commit Phase I: Preparation
Coordinator receives a commit request.
Coordinator instructs all resource managers to get ready to “go either way” on the transaction. Each resource manager writes all updates from that transaction to its own physical log.
Coordinator receives replies from all resource managers. If all are ok, it writes commit to its own log; If not then it writes rollback to its log.
Database Management Systems

20. Two - Phase Commit Phase 2: Final Commit
Coordinator then informs each resource manager of its decision and broadcasts a message to either commit or rollback (abort.) If the message is commit, then each resource manager transfers the update from its log to its database.
A failure during the commit phase puts a transaction “in limbo.” This has to be tested for and handled with timeouts or polling.
Database Management Systems

21. 3. Failure Transparency
Ensures that the system will continue to operate in the event of a node failure
Provides redundant functions in another network node
Limits the function lost to the single node, not the overall system
Database Management Systems

22. 4. Performance Transparency
Objective of query optimization routine is to minimize total cost associated with the execution of a request
Costs associated with a request are a function of the:
Access time (I/O) cost
Communication cost
CPU time cost
Database Management Systems

23. Query Optimization
Must provide distribution transparency as well as replica transparency
Replica transparency - hide the existence of multiple copies of data from the user
Query optimization techniques:
Manual or automatic
Static or dynamic
Statistically based or rule-based algorithms
Database Management Systems

24. 5. Heterogeneity Transparency
Allows the integration of several different local DBMS (relational, network, and hierarchical) under a common, or global, schema.
Translates all data requests from the global schema to the local DBMS schema
Database Management Systems

25. Distributed Database Design
Design principles and concepts are still applicable. The design introduces additional new issues:
Data fragmentation
How to partition the database into fragments
Data replication
Which fragments to replicate
Data allocation
Where to locate those fragments and replicas
Database Management Systems

26. Data Fragmentation
Breaks single object into two or more segments or fragments
Each fragment can be stored at any site over a computer network
Information about data fragmentation is stored in the distributed data catalog (DDC), from which it is accessed by the TP to process user requests
Database Management Systems

27. Data Fragmentation Strategies
Horizontal fragmentation:
Division of a relation into subsets (fragments) of tuples (rows)
Vertical fragmentation:
Division of a relation into attribute (column) subsets
Mixed fragmentation:
Combination of horizontal and vertical strategies
Database Management Systems

28. A Sample CUSTOMER Table
Database Management Systems

29. Horizontal Fragmentation
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30. Vertically Fragmented
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31. Mixed Fragmentation
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32. Data Replication
Storage of data copies at multiple sites served by a computer network
Fragment copies can be stored at several sites to serve specific information requirements
Can enhance data availability and response time
Can help to reduce communication and total query costs
Database Management Systems

33. Data Allocation Allocation strategies:
Centralized data allocation - entire database is stored at one site
Partitioned data allocation - database is divided into several disjointed parts (fragments) and stored at several sites
Replicated data allocation - copies of one or more database fragments are stored at several sites
Data distribution over a computer network is achieved through data partition, data replication, or a combination of both
Database Management Systems

34. Client/Server vs. DDBMS
Way in which computers interact to form a system
Features a user of resources, or a client, and a provider of resources, or a server
Can be used to implement a DBMS in which the client is the transaction processor (TP) and the server is the data process (DP)
Database Management Systems

35. Client/Server Advantages
Less expensive than alternate minicomputer or mainframe solutions
Allow end user to use microcomputer’s GUI, thereby improving functionality and simplicity
More people with PC skills than with mainframe skills in the job market
PC is well established in the workplace
Numerous data analysis and query tools exist to facilitate interaction with DBMSs available in the PC market
Considerable cost advantage to offloading applications development from the mainframe to powerful PCs
Database Management Systems

36. Client/Server Disadvantages
Creates a more complex environment, in which different platforms (LANs, operating systems, and so on) are often difficult to manage
An increase in the number of users and processing sites often paves the way for security problems
Possible to spread data access to a much wider circle of users increases demand for people with broad knowledge of computers and software increases burden of training and cost of maintaining the environment
Database Management Systems

37. Twelve Commandments for Distributed Databases
Local site independence
Central site independence
Failure independence
Location transparency
Fragmentation transparency
Replication transparency
Distributed query processing
Distributed transaction processing
Hardware independence
Operating system independence
Network independence
Database independence
Database Management Systems

38. Wrap Up ER Model Normalization, SQL Database design
Entity and relationship, Cardinality
Transforming ERD into relations
Normalization,
Functional dependency
1NF, 2NF, 3NF
SQL
DDL & DML
Create, insert, update, delete
Select, group by, where vs. having, join
Aggregate function
Two or more table (normal) Join and outer join
Database design
conceptual, logical, physical
ODBC and JDBC
Database Management Systems

39. Wrap Up Database warehouse XML DBA Transaction Process
DSS data characteristics, database characteristics, OLAP vs. OLTP
Star schema: fact table and dimension table
XML
Well-formed XML, Valid XML, DTD
DBA
Oracle data dictionary
Privileges: system & object privileges, role
Transaction Process
Transaction, transaction log
Concurrent control and potential problems
Deadlock, deadlock control
Distributed Database
Characteristics, two-phase commit
Transparency features
Database Management Systems