Distributed Databases: Review May 2003Yangjun Chen1 Distributed Databases System Architecture Distributed Database Design Semantic Data Control Distributed

May 2003 Yangjun Chen 1

Distributed Databases: Review

Distributed Databases

System

Architecture

Distr ibu ted D

at ab aseD

esign

Sem

antic Data

Control

Distributed T

ransactionM

anagement

Distributed Q

ueryP

rocessing



System Architecture

ANSI/SPARC Architecture

DBMS Implementation Alternatives

Datalogical Architecture

Clients/Server Architecture

Components of a Multi-DBMS























Distributed DBMS Design

Relation Fragmentation

Horizontal, Vertical, Hybrid

Correctness of Fragmentation

Completeness, Reconstruction, Disjointness

AlgorithmsCOM_MIN Al. , Bond Energy Al.

Fragment Allocation















Algorithms for horizontal fragmentation:

COM_MIN AlgorithmGiven a relation and a set of predicates, it will find acomplete and minimal set of predicates

Horizontal AlgorithmGiven a complete and minimal set of predicates, it willproduce a horizontal fragmentation































Global affinity measure:

GAM = aff(Ai, Aj)*[aff(Ai, Aj-1) + aff(Ai, Aj+1) +

aff(Ai-1, Aj) + aff(Ai+1, Aj)]

Since the affinity matrix is symmetric, we have

GAM = 2 * aff(Ai, Aj)*[aff(Ai, Aj-1) + aff(Ai, Aj+1 )]

AM = aff(Ai, Aj)*[aff(Ai, Aj-1) + aff(Ai, Aj+1 )]

1i 1j

1i 1j

1i 1j



Global affinity measure:

AM = aff(Ai, Aj)*[aff(Ai, Aj-1) + aff(Ai, Aj+1)]

= [aff(Ai, Aj)*aff(Ai, Aj-1) + aff(Ai, Aj)*aff(Ai, Aj+1)]

= [ aff(Ai, Aj)*aff(Ai, Aj-1) + aff(Ai, Aj)*aff(Ai, Aj+1)]

= [bond(Ai, Aj-1) + bond(Ai, Aj+1)],

Where bond(Ax, Ay) = aff(Az, Ax)*aff(Az, Ay).

ni 1

1i 1i

nj 1

nz 1

nj 1

nj 1

nj 1

ni 1



Relation schema:

R[A1, …, Ai, …, Aj, …, Ak-1, Ak, …, An]

Affinity matrix:

A1, …, Ai, …, Aj, …, Ak-1, Ak, …, An

…… … …… … …… ……

Clustered affinity matrix:

Ai1, …, Ail, Ai , Aj, Ai(l+3), …, Ai(k-1) Ai1, …, Ail, Ai , Ak , Aj, Ai(l+3), …,

…… …… …… …… …… ……

oldold newnew



AMAMoldold = = [bond(Ais, Ai(s-1)) + bond(Ais, Aj(s+1))] + bond(Ai, Ail) + bond(Ai, Aj) + bond(Aj, Ai) + bond(Aj, Ai(l+3)) + [bond(Ais, Ai(s-1)) + bond(Ais, Aj(s+1))]

AMAMnewnew = = [bond(Ais, Ai(s-1)) + bond(Ais, Aj(s+1))] + bond(Ai, Ail) + bond(Ai, Ak) + bond(Ak, Ai) + bond(Ak, Aj) + bond(Aj, Ak) + bond(Aj, Ai(l+3)) + [bond(Ais, Ai(s-1)) + bond(Ais, Aj(s+1))]

AMAMnewnew – AMAMold old = = 2* 2* bond(Ai, Ak) + 2* bond(Aj, Ak) – 2* bond(Ai, Aj)

ls 1

13

kls

ls 1

13

kls



























total cost

cost for query processing cost for storage

cost for data processing cost for transmission

cost fordata access

cost forintegritychecking

cost forconcurrencycontrol

update cost retrieval cost



Semantic Data Control

View Management

Data Security

Semantic Integrity Control

Constraint Specification Language

Integrity Enforcement





















Distributed Query Processing

Query Processing Methodology

- Query Decomposition

- Data Localization

- Global Optimization

- Local Optimization

































R* Algorithm

SDD-1 Algorithm



























Distributed Transaction Management

Transaction Concepts and Models

Distributed Concurrency Control

Distributed 2PL

Timestamp Ordering

Optimistic Concurrency Control

Deadlock

























Phenomena description

P1 dirty read (transaction can read data that is not committed)

P2 nonrepeatable read(transaction can read the same row twice, and it could be different)

P3 phantom



Phenomena occurs?

P1 P2 P3

serializable no no no

repeatable read no no yes

read committed no yes yes

read uncommitted yes yes yes













































Documents

Distributed Databases: Review May 2003Yangjun Chen1 Distributed Databases System Architecture Distributed Database Design Semantic Data Control Distributed