Consistent Data Replication: Is it feasible in WANs?

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Consistent Data Replication: Is it feasible in WANs? Yi Lin Bettina Kemme Marta Patiño-Martínez Ricardo Jiménez-Peris Sep 2, 2005

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Consistent Data Replication: Is it feasible in WANs?. Yi Lin Bettina Kemme Marta Patiño-Martínez Ricardo Jiménez-Peris Sep 2, 2005. Data Replication: What,Why,How?. Without Replication. With Replication. Toronto. Montreal. Ottawa. Toronto. Montreal. Ottawa. …. …. WAN. Montreal. - PowerPoint PPT Presentation

Transcript of Consistent Data Replication: Is it feasible in WANs?

Page 1: Consistent Data Replication: Is it feasible in WANs?

Consistent Data Replication: Is it feasible in WANs?

Yi LinBettina Kemme

Marta Patiño-Martínez Ricardo Jiménez-Peris

Sep 2, 2005

Page 2: Consistent Data Replication: Is it feasible in WANs?

Data Replication: What,Why,How?

… …

Montreal MontrealToronto Ottawa

TorontoToronto MontrealMontreal OttawaOttawa

Without Replication With Replication

Benefits: Fault Tolerance, Performance Challenge: keep data consistent

WAN

Page 3: Consistent Data Replication: Is it feasible in WANs?

Data Replication: challenge

w(x) w(x)

xx xx xx

Replica control

• Keep data consistent

Page 4: Consistent Data Replication: Is it feasible in WANs?

Motivations

• Most replication protocols have been proved to perform well in LANs.

• Little work has been done in WANs– GlobData [DMBS02], Tech Report [JHU02]

• Are these protocols also feasible in WANs?– Protocols working well in LANs may not work well in

WANs.

• Why? What are the bottlenecks?• Any solutions?

Page 5: Consistent Data Replication: Is it feasible in WANs?

Intro to Group Communication Systems

• GCS provides – multicast primitives to all members in the group– Group maintenance (removal of failed members, etc.)

• Ordering– Unordered– Total order (messages delivered in all members in the

same order)

• Reliability– Different degrees of delivery guarantees in case of

site failures– Analyzed in paper;

Page 6: Consistent Data Replication: Is it feasible in WANs?

Data Replication: Using Group Communication Systems

xxx x

w(x)w(x)

w(x) w(x)

x x

Total Order

• Read-Only requests:• Executed in the local site

• Update requests: • Multicast in total order

firstly.• executed according to total

order delivery.• Num of msgs for an update

• 1 total order

w(x)w(x)

Symmetric

Page 7: Consistent Data Replication: Is it feasible in WANs?

Data Replication: Using Group Communication Systems

xxx x

w(x)w(x)

w(x) w(x)

x x

Total Order

• Read-Only requests:• Executed in the local site

• Update requests: • Request totally ordered firstly.• executed only in the primary

site• Multicast the changes in

unordered msg.• Apply change in other sites

• Num of msgs for an update• 1 total order + 1 unordered• Local write (w(x))

•1 total order within response time

• Remote write (w(x))•1 total order + 1 unordered within response time

w(x)w(x) primary

Primary Copy

unordered

Page 8: Consistent Data Replication: Is it feasible in WANs?

Data Replication: Using Group Communication Systems

xxx x

w(x)w(x)

w(x) w(x)

x x

Total Order

• Read-Only requests:• Executed in the local site

• Update requests: • Request totally ordered firstly.• executed locally• Multicast the changes in

unordered msg.• Apply change in other sites

• Num of msgs for an update• 1 total order + 1 unordered• No concurrent conflicting req

•1 total order within response time

• Has concurrent conflicting req•1 total order + 1 unordered within response time

w(x)w(x)

Local Copy

unordered

Page 9: Consistent Data Replication: Is it feasible in WANs?

Num of messages summary

Symmetric Primary Copy Local Copy

Total num of msgs

1 total order 1 total order

1 unordered

1 total order

1 unordered

Num of msgs within respone time

1 total order Local write

1 total order

No concurrent conflicting request

1 total order

Remote write

1 total order

1 unordered

Has concurrent conflicting request

1 total order

1 unordered

Page 10: Consistent Data Replication: Is it feasible in WANs?

Experiment (I)

0

20

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40 60 80 100 120 140 160Load (txn/s)

Res

p Ti

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(ms)

PCSymLC

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5 15 25 35 45Load (txn/s)

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SymPC-LWLCPC-RW

LAN WAN

(5 sites, 100% update)

Page 11: Consistent Data Replication: Is it feasible in WANs?

Experiment (I): Response time analysis

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PC-RW10

LC10 Sym20 PC-LW20

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ms)

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Page 12: Consistent Data Replication: Is it feasible in WANs?

Experiment (II): Scalability in WAN

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Read-only requests Update requests

Page 13: Consistent Data Replication: Is it feasible in WANs?

Different Total Order Algorithms

SEQUENCER

mA (seq)

B

C

TOKEN

mA

B

C

token

LAMPORT

mA

B

C

<1,0,0>

<1,0,0>

<1,0,0>

Round Robin (ATOP)

m1A

B

C

m2

Seq #

m2m1

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Experiment (III): Different Total Order Alg

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SEQRRLAMPTOKEN

5 sites in WAN, with replication100% update, Symmetric,

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5 sites in WAN, without replication

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Conclusions

• Consistent database replication is feasible in WANs;

• In WANs, – For deterministic applications, Symmetric approach is

preferable. – For non-deterministic applications, Local Copy is

preferable;

• In WAN, total order multicast is crucial to response time. Round Robin total order has better performance over others;

• We have some other interesting optimizations. Please refer to our paper.

Page 16: Consistent Data Replication: Is it feasible in WANs?

References• [C-JDBC] E. Ceccet, J.Marguerite, and W. Zwaenepoel. C-JDBC:

Flexible database clustering middleware. In USENIX conference 2004

• [Ganymed] C. Plattner and G. Alonso. Ganymed: Scalable replication for transactional web applications. In Middleware, 2004.

• [GlobData] L. Rodrigues, H. Miranda, R. Almeida, J. Martins, and P. Vicente. Strong Replication in the GlobData Middleware. In Workshop on Dependable Middleware-Based Systems, 2002.

• [Middle-R] R. Jimenez-Peris, M. Patiòno-Martnez, B. Kemme, and G. Alonso. Improving Scalability of Fault Tolerant Database Clusters. In ICDCS'02.

• [Conflict-Aware] C. Amza, A. L. Cox, and W. Zwaenepoel. Conict-Aware Scheduling for Dynamic Content Applications. In USENIX Symp. on Internet Tech. and Sys., 2003.

• [State Machine] F. Pedone, R. Guerraoui, and A. Schiper. The Database State Machine Approach. Distributed and Parallel Databases, 14:71-98, 2003.

• [Spread] http://www.spread.org• [JGroups] http://www.jgroups.org