EMP
L1
Eno, Ename, Title
L2
ASG
L3
Eno, Jno, Resp, Dur
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HF -Appl. Info. : Simple Predicates
Predicates used in user queries.

Given R(A1 , A2 , ..., An ), with each Ai having domain of values Di Simple predicate pj defined on R has the form
User Input
LIS’s
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Distribution Design Issues
Fragmentation

Why fragmentation at all How to fragment How much to fragment How to test correctness
Not-replicated
Each fragment reside at only one site
What
are the advantages and disadvantages?
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Allocation Alternatives: Pros and Cons
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Top-Down Design Process
User Input
Requirement Analysis
Objectives
User Input
Conceptual Design GCS
View Integration
View Design ES’s
Access Information Distribution Design LCS’s Physical Design
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Information Req源自irements Four
categories
Database information.
Application information. Communication network information.
Computer system information.
Disjointness
If relation R is decomposed into fragments R1, R2, …, Rn
and data item di is in Rj, then di should not be in any other fragment Rk (k!=j).
– Mixed/Hybrid Fragments -combination of above two.
How
much to fragment
Too little -too much of irrelevant data access. Too much -too much processing cost. Need to find suitable level of fragmentation.
priority.
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Dimensions of the Problem
Access pattern behavior
Dynamic Static Complete Information
Data Data + Program Level of knowledge Partial Information
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Allocation Alternatives
Full
Replication.
Replication (Partitioned)
Each fragment reside at each site
Partial
Each fragment reside at some of the sites
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HF -Database Information
The global schema
PAY Title, Sal
Owner and member relations
Cardinality of each relation
PROJ Jno, Jname, Budget. Loc
Full-Replication Partial -replication Partitioning Query Processing Directory Management Concurrency Control Reliability Reality Easy Easy or non-existent Moderate High Possible application Same Difficulty Same Difficulty Difficult High Realistic Easy Low Possible application
is an operator =, <, >, , , and ; Value Di
Pj : Ai Value
Example:
Jname=“maintenance” Budget 200000
Follow ``80/20'' rule
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About fragmentation
How
should we fragment
Vertical Fragments -sub grouping of the attributes. Horizontal Fragments -sub grouping of the tuples.
HF -Appl. Info. : Minterm Predicates

Given a set Pr = {p1, p2, ..., pm} of simple predicates for relation Ri , the set of minterm predicates M = {m 1, m 2 , ..., m z } defined as
L3: DDBS Design
1. 2.
Introduction Fragmentation
1) Horizontal fragmentation
2) Vertical fragmentation
3.
Allocation
L3-1 DDBS Design -- 1
Distributed Database Design
the distribution of DDBMS software distribution of applications
We
concentrate on distribution of data.
The distribution of DDBMS and applications are given a
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Horizontal Fragmentation (HF)
Primary
horizontal fragmentation (PHF) based on predicates accessing the relation. Derived horizontal fragmentation (DHF) based on predicates being defined on another logically related relation. We shall first study algorithm for horizontal fragmentation, and then study issues related to derived horizontal fragmentation.
Allocation Information
requirements
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Why fragment at all?
Unit
of distribution = unit of data application accesses. Reduce irrelevant data access. Facilitates intra-query concurrency. Can be used with other performance enhancing methods, such as, indexing and clustering Applications have conflicting requirements making disjoint fragmentation very hard problem. Multiple fragment access requires join or union. Semantic data control (integrity enforcement) could be very costly.
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Correctness Criteria
Completeness
-no loss of data.
Decomposition of relation R into fragments R1, R2, …, Rn
is complete if and only if each data item in R can also be found in some Ri .