Lecture 1 ddbms

Lecture December 21, 2011

Distributed Database
Management System
By
Mangesh R. Wanjari
Asst. Professor, Department of CSE
Shri Ramdeobaba College of Engineering and Management, Nagpur

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
- Computational capacity of Personal Computers
- Internet and the World Wide Web used for data access
and distribution
- Data analysis through data mining and data warehousing

Wednesday, Dcember 21, 2011 Distributed Database Systems 2

Overview

• What and why?
• The Distributed Database Management Systems
• The Reference Architecture for Distributed Databases
• Data Fragmentation,
• Distributed Transparency
• Distributed Database Design


Definition
• A distributed database (DDB) is a collection of
multiple, logically interrelated databases distributed
over a computer network.
• A distributed database management system (DDBMS)
is the software that manages the DDB and provides an
access mechanism that makes this distribution
transparent to the users.
• Distributed database system (DDBS) = DDB + D–DBMS


Features of Distributed Versus Centralized Databases

• Centralized Control
• Data Independence
• Reduction in Redundancy
• Complex Physical Structures and efficient
access
• Integrity, Recovery, and Concurrency control
• Privacy and Security


Why Distributed Databases

• Organizational and economic reasons
• Interconnection of existing databases
• Incremental growth
• Reduced communication overhead
• Performance considerations
• Reliability and availability


Overview

• What and why?


Introduction
• The traditional database approach keeps all data
centrally and then accesses them mostly in a client
server model
• in a distributed database system data are distributed
over site geographically
• Say for example there are four branches of a bank at
different sites
• There will be two types of transaction, one is local
transaction and the other is global transaction
• In global transaction case the program has to access
data over site, which needs much attention, such as,
transaction over network, speed, efficient access,
integrity, recovery, concurrency control, privacy,
security and a lot of things


Centralized Database Management System


Distributed Processing Environment


Distributed Database Environment


Traditional distributed processing architecture

CLIENT CLIENT
LAN CLIENT CLIENT

LAN
CLIENT CLIENT
CLIENT CLIENT

Nagpur Mumbai

CLIENT CLIENT CLIENT CLIENT
LAN LAN

DBMS
CLIENT CLIENT CLIENT
CLIENT

Delhi Bangalore


Distributed Database Architecture

CLIEN
T
LAN

DBMS
DBMS


Mumbai
Nagpur

CLIENT
CLIEN CLIENT CLIENT CLIENT
T
LAN

DBMS
DBMS


Delhi Bangalore


Distributed Database Management System

Components of a Distributed DBMS Possible access methods


Overview

• What and why?


Reference Architecture for Distributed DBMS

The reference model has two
main parts

1. Site independent schemas
2. Site dependent schemas


FRAGMENTS AND PHYSICAL IMAGES FOR A GLOBAL RELATION


What is so fascinating about this architecture?

The most important three features that motivates in
designing this architecture are

• Separation of data fragmentation and allocation.

• The control of redundancy.

• The independence from local DBMS.


Overview

• What and why?


Types of Data Fragmentation

• Horizontal Fragmentation
• Vertical Fragmentation
• Hybrid/Mixed Fragmentation

There are some rules that must be followed when
defining fragments:

• Completeness condition
• Reconstruction condition
• Disjointness condition


Horizontal Fragmentation
Let a global relation be
SUPPLIER (SUM, NAME, CITY)

Here the SUPPLIER contains supplier number, supplier name and the city
where the supplier lives. However if the entire supplier comes from Nagpur
city (“NGP”) and Mumbai city (“MUM”) then the horizontal fragmentation can
be defined in the following way:

SUPPLIER1 = SL CITY = ”NGP” SUPPLIER
SUPPLIER2 = SL CITY = ”MUM” SUPPLIER

It is always possible to reconstruct the SUPPLIER global relation through the
union operation:

SUPPLIER = SUPPLIER1 UN SUPPLIER2

q1: CITY=“NGP” AND q2: CITY=“MUM”


Horizontal Fragmentation CNTD..
A1 A2 ………. An
T1
A1 A2 ………. An T2
T1 T3
1
T2 .
1
T3 .T60
1
. 2 Site 1
.T60
2
T61
A1 A2 ………. An
3
T61
.
3
.
.
3
.
Tn
Tn

Site 2
Derived Horizontal Fragmentation
SUPPLY(SNUM, PNUM, DEPTNUM, QUAN)

SUPPLY1 =SUPPLY SJ SNUM =SNUM SUPPLIER1

SUPPLY2 =SUPPLY SJ SNUM =SNUM SUPPLIER2


VERTICAL FRAGMENTATION
A1 A2 A3 A4
Original t1 How to Reconstruct:
(R)
Relation t2 R=Rs1 Rs2 Rsn

TID –Tuple ID
Hidden Attribute to
ensure account tn
and simple join
reconstruction
A1 A2 TID TID A3 A4 RS2
RS1 t1 1 1 t1
t2 2 2 t2
RS1.TID=RS2.TID
n n
tn tn Join condition

SITE1 SITE2


VERTICAL FRAGMENTATION
EMPLOYEE (EMPNUM, SAL, TAX, MGRNUM, DEPTNUM)

A vertical fragmentation of this relation can be defined as

EMPLOYEE1 = PJ EMPNUM, NAME, MGRNUM, DEPTNUM EMPLOYEE
EMPLOYEE2 = PJ EMPNUM, SAL, TAX EMPLOYEE

The fragmentation could, for instance, reflect an organization in which
salaries and taxes are managed separately. The reconstruction of relation
EMPLOYEE can be obtained as

EMPLOYEE = EMPLOYEE1 JN EMPNUM = EMPNUM EMPLOYEE2


MIXED FRAGMENTATION
Rs1 A4 A5
A1 A2 A3 Rs3
u
R s
a
A1 A2 A3 A4 A5

Rs2
A1 A2 A3 E
A4 A5 u
(Salary (Benefit r
Attributes) Attributes)
o
p
Rs4 e

MIXED FRAGMENTATION
EMPLOYEE (EMPNUM, NAME, SAL, TAX, MGRNUM, DEPTNUM)

The following is a mixed fragmentation that is obtained by applying the
vertical fragmentation of the previous example, followed by a
horizontal fragmentation on DEPTNUM:

EMPLOYEE1 = SL DEPTNUM <= 10 PJ EMPNUM, NAME, MGRNUM, DEPTNUM EMPLOYEE
EMPLOYEE2 = SL 10 < DEPTNUM <= 20 PJ EMPNUM, NAME, MGRNUM, DEPTNUM
EMPLOYEE
EMPLOYEE3 = SL DEPTNUM > 10 PJ EMPNUM, NAME, MGRNUM, DEPTNUM EMPLOYEE
EMPLOYEE4 = PJ EMPNUM, NAME, SAL, TAX EMPLOYEE

The reconstruction of relation EMPLOYEE is defined by
the following expression:

EMPLOYEE = UN (EMPLOYEE1, EMPLOYEE2, EMPLOYEE3)
JN EMPNUM=EMPNUM PJ EMPNUM, SAL, TAX EMPLOYEE4


Overview

• What and why?


Transparencies as seen by simple application
Fragmentation transparency

Select NAME into $NAME
from SUPPLIER
where SNUM=$SNUM

Location transparency

Local Mapping
transparency


Transparencies as seen by simple application

No transparency


Topics left for you from the syllabus

• Distributed database access primitives

• Integrity constraints in Distributed databases


Overview

• What and why?


Distributed Database Design

Any database design has following issues to be
addressed

1. Designing the conceptual schema
2. Designing the physical storage

Distribution of data also add to this

3. Designing how to fragment data
4. Designing how to allocate fragments to sites



Objectives of the design of data distribution

• Process locality
• Availability and reliability of distributed data
• Workload distribution
• Storage cost and availability
• Distributed database design



Two approaches to design

1. Top-down approach
• start by designing the global schema, and we proceed by designing the
fragmentation of the database, and then allocating the fragments to the
sites, creating the physical images
• Suitable for systems which are developed from scratch

2. Bottom-up approach
• The selection of a common database model for describing the global
schema of the database.
• The translation of each local schema into the common data model.
• The integration of the local schemata into a common global schema.


The Design of Database Fragmentation

Horizontal Fragmentation (Primary)

Let P={p1,p2,…,pn} be a set of simple predicates. In order
for P to represent fragment correctly and efficiently, P
must be complete and minimal

1. We say that a set P is complete iff any two tuples
belonging to the same fragment are referenced with
same probability by any application.
2. We say the set P is minimal if all its predicates are
relevant.



Horizontal Fragmentation (Derived)

• A distributed join is a join between horizontally fragmented relations
which is represented by Join Graphs
• Join Graphs
• Total
• Reduced
• Simple
• Partitioned

Derived Fragments : Ri=Si SJF R



Vertical Fragmentation

1. Split approach
2. Grouping approach



Mixed Fragmentation

1. Applying Vertical Fragmentation to Horizontal
fragments

2. Applying Horizontal Fragmentation to Vertical
fragments


The Allocation of Fragments

General criteria for fragment allocation

1. Redundant
2. Non-Redundant

If replicated complexity is high because
1. The degree of replication of each fragment becomes a
variable of the problem.
2. Modeling read applications is complicated by the fact that
the applications can now select among several alternative
sites for accessing fragments


The Allocation of Fragments

For determining the redundant allocation of fragments,
either of the following methods can be used:

1. All beneficial sites: In this approach the set of all sites
where the benefit of allocation one copy of the fragment
is higher than the cost, and allocate a copy of the
fragment to each element of this set.

1. Additional replication: Here first the solution of the non
replicated problem, and then progressively introduce
replicated copies starting from the most beneficial; the
process is terminated when no additional replication is
beneficial.


Measure of costs and benefits of fragment allocation

Some Definitions

• i is the fragment index
• j is the site index
• k is the application index
• fkj is the frequency of application k at site j
• rki is the number of retrieval references of
application k to fragment I
• uki is the number of update references of
application k to fragment I
• nki = rki - uki


Horizontal fragmentation:

1. Using the ‘best-fit’ approach for a non-replicated allocation, we place Ri at the
site where the number of references to Ri is maximum. The number of local
references of Ri at site j is
Bij = ∑k fkj nki
Ri is allocated at site j* such that Bij* is maximum.

2. Using the ‘all beneficial sites’ method for replicated allocation, we place Ri at
all sites j where the cost of retrieval references of applications is larger than
the cost of update references to Ri from applications at any other site. Bij is
evaluated as the difference:
Bij = k fkj rki – C *∑k∑ j≠j fkj’ uki
C is a constant which measures the ratio between the cost of an update and
retrieval access



3. Using the ‘additional replication’ method for replicated allocation, we can
measure the benefit of placing a new copy of Ri in terms of increased
reliability and availability of the system.

Let di denote the degree of redundancy of Ri, and let Fi denote the benefit of
having Ri fully replicated at each site. The following function was introduced to
measure this benefit:
β(di) = (1 – 21-di) Fi
Note that β(1) = 0, β(2) = Fi / 2, β(3) = 3 Fi / 4, and so on.
We evaluate the benefit of introducing a new copy of Ri at site j by modifying the
formula of case 2 as follows:
Bij = k fkj rki – C *∑k∑ j≠j fkj’ uki + β(di)


References

1. “Distributed databases Principals & Systems”, Stefano Ceri,
Ginseppe Pelagatti, McGrawHill Book Company, 1984.

2. ”Database System Concepts”, Abraham Silberschatz, Henry F.
Korth, S. Sudarshan, Third Edition,The McGraw Hill
Companies, Inc, 1997.

3. Database Systems- Design, Implementation and Management;
Peter Rob, Carlos Coronnel; Course Technology; 2000

4. Principles of Distributed Database Systems , M. T. Özsu and P.
Valduriez, 3rd edition, Springer, 2011


Motivation is what gets you started and Habit is what keeps you going…

Thanks a lot for patient listening!!

Questions?

You can reach me at
mangeshwanjari[at]gmail.com


Lecture 1 ddbms

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