Database Principles: Fundamentals of Design, Implementation, and Management. 3rd Edition. Chapter 14 Distributed Databases.

1. Database Principles 3rd Ed., Coronel, Morris, Crockett, Blewett
©2020 Cengage EMEA
Database Principles
Fundamentals of Design,
Implementation, and Management
Carlos Coronel, Steven Morris,
Keeley Crockett, Craig Blewett
CHAPTER 14
DISTRIBUTED DATABASES

2. Database Principles 3rd Ed., Coronel, Morris, Crockett, Blewett
©2020 Cengage EMEA
In this chapter, you will learn:
• 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

3. Database Principles 3rd Ed., Coronel, Morris, Crockett, Blewett
©2020 Cengage EMEA
The Evolution of Distributed Database
Management Systems
• Distributed database management system
(DDBMS)
– Governs storage and processing of logically related
data over interconnected computer systems in
which both data and processing functions are
distributed among several sites

4. Database Principles 3rd Ed., Coronel, Morris, Crockett, Blewett
©2020 Cengage EMEA
The Evolution of Distributed Database
Management Systems (continued)
• Centralised database required that corporate
data be stored in a single central site
• Dynamic business environment and
centralised database’s shortcomings spawned
a demand for applications based on data
access from different sources at multiple
locations

5. Database Principles 3rd Ed., Coronel, Morris, Crockett, Blewett
©2020 Cengage EMEA
The Evolution of Distributed
Database Management Systems
(continued)

6. Database Principles 3rd Ed., Coronel, Morris, Crockett, Blewett
©2020 Cengage EMEA
DDBMS Advantages and Disadvantages
• Advantages include:
– Data are located near “greatest demand” site
– Faster data access
– Faster data processing
– Growth facilitation
– Improved communications

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Database Principles 3rd Ed., Coronel, Morris, Crockett, Blewett
©2020 Cengage EMEA
DDBMS Advantages and Disadvantages
(continued)
• Advantages include (continued):
– Reduced operating costs
– User-friendly interface
– Less danger of a single-point failure
– Processor independence

8. Database Principles 3rd Ed., Coronel, Morris, Crockett, Blewett
©2020 Cengage EMEA
DDBMS Advantages and Disadvantages
(continued)
• Disadvantages include:
– Complexity of management and control
– Security
– Lack of standards
– Increased storage requirements
– Increased training cost
– Higher Costs

9. Database Principles 3rd Ed., Coronel, Morris, Crockett, Blewett
©2020 Cengage EMEA
Distributed Processing and Distributed
Databases

10. DDBMS Advantages and Disadvantages
(continued)

11. Database Principles 3rd Ed., Coronel, Morris, Crockett, Blewett
©2020 Cengage EMEA
Characteristics of Distributed
Management Systems
• Application interface
• Validation
• Transformation
• Query optimisation
• Mapping
• I/O interface

12. Database Principles 3rd Ed., Coronel, Morris, Crockett, Blewett
©2020 Cengage EMEA
Characteristics of Distributed
Management Systems (continued)
• Formatting
• Security
• Backup and recovery
• DB administration
• Concurrency control
• Transaction management

13. Database Principles 3rd Ed., Coronel, Morris, Crockett, Blewett
©2020 Cengage EMEA
Characteristics of Distributed
Management Systems (continued)
• Must perform all the functions of centralised
DBMS
• Must handle all necessary functions imposed
by distribution of data and processing
– Must perform these additional functions
transparently to the end user

14. Database Principles 3rd Ed., Coronel, Morris, Crockett, Blewett
©2020 Cengage EMEA
Characteristics of Distributed
Management Systems (continued)

15. Database Principles 3rd Ed., Coronel, Morris, Crockett, Blewett
©2020 Cengage EMEA
DDBMS Components
• Must include (at least) the following
components:
– Computer workstations
– Network hardware and software
– Communications media
– Transaction processor (application processor,
transaction manager)
• Software component found in each computer that
requests data

16. Database Principles 3rd Ed., Coronel, Morris, Crockett, Blewett
©2020 Cengage EMEA
DDBMS Components (continued)
• Must include (at least) the following
components (continued):
– Data processor (DP)
– Software component residing on each computer
that stores and retrieves data located at the site
• May be a centralised DBMS

17. DDBMS Components (continued)

18. Database Principles 3rd Ed., Coronel, Morris, Crockett, Blewett
©2020 Cengage EMEA
Levels of Data and Process
Distribution

19. Database Principles 3rd Ed., Coronel, Morris, Crockett, Blewett
©2020 Cengage EMEA
Single-Site Processing, Single-Site
Data (SPSD)
• In the single-site processing, single-site data
(SPSD) scenario, all processing is done on a
single host computer and all data are stored
on the host computer’s local disk.
• The DBMS is located on the host computer,
which is accessed by dumb terminals.
• TP and the DP are embedded within the
DBMS.

20. Database Principles 3rd Ed., Coronel, Morris, Crockett, Blewett
©2020 Cengage EMEA
Single-Site Processing, Single-Site Data
(SPSD) (continued)

21. Database Principles 3rd Ed., Coronel, Morris, Crockett, Blewett
©2020 Cengage EMEA
Multiple-Site Processing,
Single-Site Data (MPSD)
• Multiple processes run on different computers
sharing single data repository
• MPSD scenario requires a network file server
running conventional applications that are
accessed through a network.
• Many multiuser accounting applications,
running under personal computer network, fit
such a description

22. Database Principles 3rd Ed., Coronel, Morris, Crockett, Blewett
©2020 Cengage EMEA
Multiple-Site Processing, Single-Site Data
(MPSD) (continued)

23. Database Principles 3rd Ed., Coronel, Morris, Crockett, Blewett
©2020 Cengage EMEA
Multiple-Site Processing, Multiple-Site
Data (MPMD)
• Fully distributed database management
system with support for multiple data
processors and transaction processors at
multiple sites
• Classified as either homogeneous or
heterogeneous
• Homogeneous DDBMSs
– Integrate only one type of centralised DBMS over
a network

24. Database Principles 3rd Ed., Coronel, Morris, Crockett, Blewett
©2020 Cengage EMEA
Multiple-Site Processing, Multiple-Site
Data (MPMD) (continued)
• Heterogeneous DDBMSs
– Integrate different types of centralised DBMSs
over a network
• Fully heterogeneous DDBMS
– Support different DBMSs that may even support
different data models (relational, hierarchical, or
network) running under different computer
systems, such as mainframes and microcomputers

25. Multiple-Site Processing,
Multiple-Site Data (MPMD) (continued)

26. Database Principles 3rd Ed., Coronel, Morris, Crockett, Blewett
©2020 Cengage EMEA
Distributed Database Transparency
Features
• Allow end user to feel like database’s only user
• Features include:
– Distribution transparency
– Transaction transparency
– Failure transparency
– Performance transparency
– Heterogeneity transparency

27. Database Principles 3rd Ed., Coronel, Morris, Crockett, Blewett
©2020 Cengage EMEA
Distribution Transparency
• Allows management of physically dispersed
database as though it were a centralised
database
• Following three levels of distribution
transparency are recognised:
– Fragmentation transparency
– Location transparency
– Local mapping transparency

28. Database Principles 3rd Ed., Coronel, Morris, Crockett, Blewett
©2020 Cengage EMEA
Distribution Transparency (continued)

29. Database Principles 3rd Ed., Coronel, Morris, Crockett, Blewett
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Distribution Transparency (continued)

30. Database Principles 3rd Ed., Coronel, Morris, Crockett, Blewett
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Transaction Transparency
• Ensures database transactions will maintain
distributed database’s integrity and
consistency

31. Database Principles 3rd Ed., Coronel, Morris, Crockett, Blewett
©2020 Cengage EMEA
Distributed Requests and
Distributed Transactions
• Distributed transaction
– Can update or request data from several different
remote sites on network
• Remote request
– Lets single SQL statement access data to be
processed by single remote database processor
• Remote transaction
– Accesses data at single remote site

32. Database Principles 3rd Ed., Coronel, Morris, Crockett, Blewett
©2020 Cengage EMEA
Distributed Requests and
Distributed Transactions (continued)
• Distributed transaction
– Allows transaction to reference several different
(local or remote) DP sites
• Distributed request
– Lets single SQL statement reference data located
at several different local or remote DP sites

33. Database Principles 3rd Ed., Coronel, Morris, Crockett, Blewett
©2020 Cengage EMEA
Distributed Requests and Distributed
Transactions (continued)

34. Database Principles 3rd Ed., Coronel, Morris, Crockett, Blewett
©2020 Cengage EMEA
Distributed Requests and Distributed
Transactions (continued)

35. Database Principles 3rd Ed., Coronel, Morris, Crockett, Blewett
©2020 Cengage EMEA
Distributed Requests and Distributed
Transactions (continued)

36. Database Principles 3rd Ed., Coronel, Morris, Crockett, Blewett
©2020 Cengage EMEA
Distributed Requests and Distributed
Transactions (continued)

37. Database Principles 3rd Ed., Coronel, Morris, Crockett, Blewett
©2020 Cengage EMEA
Distributed Requests and Distributed
Transactions (continued)

38. Database Principles 3rd Ed., Coronel, Morris, Crockett, Blewett
©2020 Cengage EMEA
Distributed Concurrency Control
• Multisite, multiple-process operations are
much more likely to create data
inconsistencies and deadlocked transactions
than are single-site systems

39. Distributed Concurrency Control
(continued)

40. Database Principles 3rd Ed., Coronel, Morris, Crockett, Blewett
©2020 Cengage EMEA
Two-Phase Commit Protocol
• Distributed databases make it possible for
transaction to access data at several sites
• Final COMMIT must not be issued until all
sites have committed their parts of
transaction
• Two-phase commit protocol requires each
individual DP’s transaction log entry be
written before database fragment is actually
updated

41. Database Principles 3rd Ed., Coronel, Morris, Crockett, Blewett
©2020 Cengage EMEA
Two-Phase Commit Protocol
• The DO-UNDO-REDO protocol is used by the DP
to roll back and/or roll forward transactions with
the help of the system’s transaction log entries.
• The DO-UNDO-REDO protocol defines three types
of operations:
– DO performs the operation and records the ‘before’
and ‘after’ values in the transaction log.
– UNDO reverses an operation, using the log entries
written by the DO portion of the sequence.
– REDO redoes an operation, using the log entries
written by the DO portion of the sequence.

42. Database Principles 3rd Ed., Coronel, Morris, Crockett, Blewett
©2020 Cengage EMEA
Performance and Failure Transparency
• Objective of query optimisation routine is to
minimise total cost associated with execution
of request
• Costs associated with request are function of:
– Access time (I/O) cost
– Communication cost
– CPU time cost
• Must provide distribution transparency as well
as replica transparency

43. Database Principles 3rd Ed., Coronel, Morris, Crockett, Blewett
©2020 Cengage EMEA
Performance and Failure Transparency
• Resolving data requests in a distributed
data environment must take the following
points into consideration:
– Data distribution.
– Data Replication
– Network and node availability.

44. Database Principles 3rd Ed., Coronel, Morris, Crockett, Blewett
©2020 Cengage EMEA
Distributed Database Design
• Data fragmentation
– How to partition database into fragments
• Data replication
– Which fragments to replicate
• Data allocation
– Where to locate those fragments and replicas

45. Database Principles 3rd Ed., Coronel, Morris, Crockett, Blewett
©2020 Cengage EMEA
Data Fragmentation
• Breaks single object into two or more
segments or fragments
• Each fragment can be stored at any site over
computer network
• Information about data fragmentation is
stored in distributed data catalog (DDC), from
which it is accessed by TP to process user
requests

46. Database Principles 3rd Ed., Coronel, Morris, Crockett, Blewett
©2020 Cengage EMEA
Data Fragmentation (continued)
• 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

47. Database Principles 3rd Ed., Coronel, Morris, Crockett, Blewett
©2020 Cengage EMEA
Data Fragmentation (continued)

48. Database Principles 3rd Ed., Coronel, Morris, Crockett, Blewett
©2020 Cengage EMEA
Data Fragmentation (continued)

49. Database Principles 3rd Ed., Coronel, Morris, Crockett, Blewett
©2020 Cengage EMEA
Data Fragmentation (continued)

50. Database Principles 3rd Ed., Coronel, Morris, Crockett, Blewett
©2020 Cengage EMEA
Data Fragmentation (continued)

51. Database Principles 3rd Ed., Coronel, Morris, Crockett, Blewett
©2020 Cengage EMEA
Data Fragmentation (continued)

52. Database Principles 3rd Ed., Coronel, Morris, Crockett, Blewett
©2020 Cengage EMEA
Data Fragmentation (continued)

53. Database Principles 3rd Ed., Coronel, Morris, Crockett, Blewett
©2020 Cengage EMEA
Data Fragmentation (continued)

54. Database Principles 3rd Ed., Coronel, Morris, Crockett, Blewett
©2020 Cengage EMEA
Data Fragmentation (continued)

55. Database Principles 3rd Ed., Coronel, Morris, Crockett, Blewett
©2020 Cengage EMEA
Data Replication
• Storage of data copies at multiple sites served
by 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

56. Database Principles 3rd Ed., Coronel, Morris, Crockett, Blewett
©2020 Cengage EMEA
Data Replication (continued)

57. Database Principles 3rd Ed., Coronel, Morris, Crockett, Blewett
©2020 Cengage EMEA
Data Replication (continued)
• Replication scenarios
– Fully replicated database
• Stores multiple copies of each database fragment at
multiple sites
• Can be impractical due to amount of overhead
– Partially replicated database
• Stores multiple copies of some database fragments at
multiple sites
• Most DDBMSs are able to handle the partially
replicated database well

58. Database Principles 3rd Ed., Coronel, Morris, Crockett, Blewett
©2020 Cengage EMEA
Data Replication (continued)
• Replication scenarios (continued)
– Unreplicated database
• Stores each database fragment at single site
• No duplicate database fragments

59. Database Principles 3rd Ed., Coronel, Morris, Crockett, Blewett
©2020 Cengage EMEA
Data Allocation
• Deciding where to locate data
• Allocation strategies
– Centralised 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

60. Database Principles 3rd Ed., Coronel, Morris, Crockett, Blewett
©2020 Cengage EMEA
Data Allocation (continued)
• Allocation strategies (continued)
– Replicated data allocation
• Copies of one or more database fragments are stored
at several sites
• Data distribution over computer network is
achieved through data partition, data
replication, or combination of both

61. Database Principles 3rd Ed., Coronel, Morris, Crockett, Blewett
©2020 Cengage EMEA
The CAP Theorem
• The initials CAP stand for the three desirable
properties
– Consistency. In a distributed database, consistency
takes a bigger role. All nodes should see the same data
at the same time, which means that the replicas
should be immediately updated.
– Availability. Simply speaking, a request is always
fulfilled by the system. No received request is ever lost.
If you are buying tickets online, you do not want the
system to stop in the middle of the operation.
– Partition tolerance. The system continues to operate
even in the event of a node failure.

62. Database Principles 3rd Ed., Coronel, Morris, Crockett, Blewett
©2020 Cengage EMEA
The CAP Theorem(continued)
• This trade-off between consistency and
availability has generated a new type of
distributed data systems in which data are
basically available, soft state, eventually
consistent (BASE).
• BASE refers to a data consistency model in
which data changes are not immediate but
propagate slowly through the system until all
replicas are eventually consistent

63. Database Principles 3rd Ed., Coronel, Morris, Crockett, Blewett
©2020 Cengage EMEA
The CAP Theorem(continued)

64. Database Principles 3rd Ed., Coronel, Morris, Crockett, Blewett
©2020 Cengage EMEA
Distributed databases within the cloud
• Cloud computing is a new style of delivering
applications, data and resources to users over the web.
It provides an alternative for organisations who do not
wish to provide their own information technology (IT)
infrastructure to host their own databases or software.
• A third party cloud provider uses a number of
interconnected and virtualised computers to supply a
range of IT services which are standardised.
• Each third party cloud provider will have its own
flexible pricing model for each service it provides.
• This is often called a service level agreement.

65. Database Principles 3rd Ed., Coronel, Morris, Crockett, Blewett
©2020 Cengage EMEA
Distributed Databases Within The
Cloud (continued)
• The main benefits to an organisation of using a cloud infrastructure are:
– Cost Effectiveness. As the third party cloud provider is likely to be
hosting services for many organisations, only one IT infrastructure is
required which reduces the cost to individual organisation.
– Latest Software. In order to remain competitive, most third party
cloud providers will ensure that their software is always the latest
version available to remain competitive.
– Scalable Architecture. If the data requirements of the organisation
expand, it is easy to increase the database capacity and/or change the
underlying data model.
– Mobile Access. Data and software within the cloud can be accessed
generally from anywhere.

66. Database Principles 3rd Ed., Coronel, Morris, Crockett, Blewett
©2020 Cengage EMEA
Distributed Databases Within The
Cloud (continued)
• Current NoSQL solutions include column stores and
document stores.
• Column stores are for large scale distributed systems
which store petrabytes of data across
• hundreds, if not thousands of servers.
– E.g. Google, for example, uses BigTable to store its
structured data for applications such as Google Earth.
• Document stores move away from storing data in
tables. Instead, each document is stored differently
depending upon its size and format. Document stores
are referred to as document-orientated databases.

67. Database Principles 3rd Ed., Coronel, Morris, Crockett, Blewett
©2020 Cengage EMEA
C. J. Date’s Twelve Commandments for
Distributed Databases
• Local site independence
• Central site independence
• Failure independence
• Location transparency
• Fragmentation transparency
• Replication transparency

68. Database Principles 3rd Ed., Coronel, Morris, Crockett, Blewett
©2020 Cengage EMEA
C. J. Date’s Twelve Commandments for
Distributed Databases (continued)
• Distributed query processing
• Distributed transaction processing
• Hardware independence
• Operating system independence
• Network independence
• Database independence

69. Database Principles 3rd Ed., Coronel, Morris, Crockett, Blewett
©2020 Cengage EMEA
Summary
• Distributed database stores logically related data in two or
more physically independent sites connected via computer
network
• Distributed processing is division of logical database
processing among two or more network nodes
• Distributed databases require distributed processing
• Main components of DDBMS are transaction processor and
data processor

70. Database Principles 3rd Ed., Coronel, Morris, Crockett, Blewett
©2020 Cengage EMEA
Summary (continued)
• Current database systems can be classified by
extent to which they support processing and
data distribution
• Homogeneous distributed database system
integrates only one particular type of DBMS
over computer network
• Heterogeneous distributed database system
integrates several different types of DBMSs
over computer network

71. Database Principles 3rd Ed., Coronel, Morris, Crockett, Blewett
©2020 Cengage EMEA
Summary (continued)
• DDBMS characteristics are best described as set of
transparencies
• Transaction is formed by one or more database requests
• Distributed concurrency control is required in network of
distributed databases
• Distributed DBMS evaluates every data request to find
optimum access path in distributed database

72. Database Principles 3rd Ed., Coronel, Morris, Crockett, Blewett
©2020 Cengage EMEA
Summary (continued)
• The design of distributed database must
consider fragmentation and replication of data
• Database can be replicated over several
different sites on computer network
• The CAP theorem states that a highly
distributed data system has some desirable
properties of consistency, availability, and
partition tolerance. However, a system can
only provide two of these properties at a time.