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Maulana Azad National Urdu University M.Tech I Semester Examination, March 2023

Paper - MTCS112PET : Distributed Databases

en

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Time : 3 hrs Marks : 70

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» V ß Z Î Ð V ” x Ó X ì è S g  á Z Š Z ® Å V / n Æ [ Z Ž C Ù X x Î z Ô zx Š z Ô w Zz z : ì Œ 6 , V ” & ] Ñ Z Î p ! 6 , t

Ž Z

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(10 x 1 = 10 Marks)

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a

/ 6 V , ì Œ

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(200)

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(5 x 6 = 30 Marks)

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a Æ w Z Î C Ù

V / 6 ,

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(500)

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5

~ x Î z

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(3 x 10 = 30 Marks)

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10

a Æ w Z Î C Ù

Zz z w

(1)

w Z Î Å

Ÿ z s

™ # ,

X

Allocation Schema (i)

H ì

?

Locks (ii)

Å

Ÿ z s

™ # ,

X

Local Schema

g Zz

Global Schema (iii)

ß

(

/

9 ) X ì C ™ x ³ 6 , ‰ Ü z Ï Z Ç ! *

Sites

x Ó Š Ž ñ ~

Distributed Database (iv)

» Ý Z E Z ì w ' ' '

'

Two Phase Commit Protocol (v)

Concurrency control can be avoided (b) Deadlock will not occur (a)

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7

(d) Atomicity, ie., all-or-nothing commits at all sites (c)

7 ì

?

(Promise)

{ ° z »

Distributed Database

‚ y à Р~ s f z g q

(vi)

Replication Transparency (b) Network Transparency (a)

Z

~ y Ð ð Ã

7

(d) Fragmentation Transparency (c)

i Ð c

Š *

¯ { Z Z

 +

X

Centralized Database

Æ

Dsitributed Database

q - Z

(vii)

Software Complexity (b) Software Cost (a)

Modular Growth (d) Slow Response (c)

g q z s f

~ Ð

¾ Z Å i Y

Š ] î ì

?

Location Transparency (viii)

Users to treat the data as if it is at one location (a) Programmers to treat the data as if it is at one location (b) Managers to treat the data as if it is at one location (c)

Z

~ y Ð ð Ã

7

(d)

2/1

(2)

g q z s f

~ Ð

¾ Z Å i Y

Š ] î ì

?

Heterogeneous Distributed Database (ix)

Same DBMS is used at each location and data are not distributed across all nodes (a) The same DBMS is used at each location and data are distributed across all nodes (b) A different DBMS is used at each location and data are not distributed across all nodes (c) A different DBMS is used at each location and data are distributed across all nodes (d)

Š g

` s f

 ~

X

All Rows

g Zz

Some Columns

Æ

Relation

6 ,

Sites

Z

(x)

Horizontal Partition (b) Data Replication (a) Horizontal and Vertical Partition (d) Vertical Partion (c)

z zx Š

Å

Disadvantages

g Zz

Advantages

Æ

Distributed Database

X , ™ s # Ÿ z Å

Distributed Database (2)

Ÿ z s

™ # , X ù

¯ 4

@ * ì

?

Performance

t ? ì H

Data Localization

~

Distributed Database (3)

z Å

Ÿ s

™ # ,

X

Transparency

Å n Z B ‚ Æ w V ƒ & o X , ™ s # Ÿ z Å ¤ S Å

Transparency

~

DDB (4)

a Æ

Y õ z Å

Ÿ s

™ # , ù X

\ M

™ ð D



ž

Serializability

~ e Æ

Concurrency Control Scheme (5)

ì c 7 *

?

Schedule Serializable

à , zZ Ð

™ ã ,

X

SIX

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Multiple Granularity (6) Lazy

g Zz

Egger

B ‚ Æ w V X N C { Z + à Æ

Data Replication

~

Distributed Database Environment (7)

z Å

Ÿ s #

™ , X Y Ð

Z V ì

?

Centralized Query Processing

t ? ì H

Distributed Query Processing (8)

à V V ß Z » E

™ w D

ƒ ñ

Ÿ z s

™ # ,

X

Distributed Query Processing Strategies

Ð ì Z o ?

ƒ

&

V

V ß

Full Join

t V Y ? ì Zg Š ™ H »

Semi Join

~

Distributed Database Environment (9)

Z » E

™ w D

ƒ ñ

Ÿ z s

™ # , X

z x Î

X , ™ s # Ÿ ?z ì Z V Y Ð

Multiversion Timestamp

t ? ì H

Multiversion Two phase Locking (10)

à , Ò Ð

™ y ,

X

Architecture Models

Æ

DDBMS

ž , ™ s # Ÿ z Å

Design Issues

Æ

DDB (11)

ƒ ä

‡ Æ . Þ ì c

*

Conflict Serializable

, ™

Check

t g Zz { Æ s Z ¤ /

Precedence

a Æ

Schedule

ñ ƒ b Š

(12)

™ ,

X

Find

Ã

Equivalent Schedule

Æ k Z ì

Conflict Serializable

¤ / Z ó 7

R1(x); r2(x); w1(y); r3(y); r2(y); w2(y); r3(w); w3(y); r4(w); r4(z) w4(w) r1(z); w1(z);

 ~ Û

™ t ,

X

Three Phase Commit Protocol

g Zz

Two Phase Commit

X , ™ p ° Å

Commit Protocol (13)

Ð ì Z Z X

n

Replications

t V Y ? ì È H » \ M Ð

Fragmentations

~

Distributed Database (14)

ñ iz V V Æ w B ‚ C N

X

(Techniques)

i § » ä ™

Fragmentations

Æ

/ / /

2/2

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