Distributed database management systems
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Distributed Database Management Systems. Reading. Textbook: Ch. 4. Design Issues. Placing of data and programs (DBMS and application) Network issues. Level of Sharing. No sharing Data sharing Data and program sharing. Heterogeneous environment!. Top-Down Design.

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Distributed database management systems

Distributed Database Management Systems


Reading

Reading

  • Textbook: Ch. 4

CSCE 824 - Spring 2011


Design issues

Design Issues

  • Placing of data and programs (DBMS and application)

  • Network issues

CSCE 824 - Spring 2011


Level of sharing

Level of Sharing

  • No sharing

  • Data sharing

  • Data and program sharing

Heterogeneous environment!

CSCE 824 - Spring 2011


Top down design

Top-Down Design

  • Global Conceptual schema  distribution

    • Fragmentation

    • Replication

    • Allocation

  • Figure 3.2

CSCE 824 - Spring 2011


Correctness of fragmentation

Correctness of Fragmentation

  • Completeness: FR={R1, …, Rn}

  • Reconstruction: R=Ri, RiR

  • Disjointness:

    • Horizontal: does not  djRisuch that djRkwhere ki

    • Vertical: same as horizontal for non-primary key attributes

1&2: Lossless-join (normalization)

CSCE 824 - Spring 2011


Data directory

Data Directory

  • Global vs. local conceptual schemas

    • How to search?

    • Where to store?

    • Single vs. multiple copies?

CSCE 824 - Spring 2011


Current research

Current Research

  • Allocation: new requirements, technology, etc.

  • Where to store the fragments?

  • Dynamic environment

    • Usage pattern

    • Application characteristics

    • Network changes

    • Security

CSCE 824 - Spring 2011


Bottom up approach

Bottom-Up Approach

  • Multi-database systems

  • How to integrate them into 1 database?

    • Interoperability

CSCE 824 - Spring 2011


Database integration

Database Integration

  • Physical integration

    • Materialized database: data warehouses

    • Extract-transform-load (ETL) tools

  • Logical integration

    • Virtual (not materialized) integration

    • Enterprise Information Integration

CSCE 824 - Spring 2011


Data warehouses

Data Warehouses

  • On-line Analytical Processing (OLAP) applications:

    • Decision support systems

    • Trend analysis and forecasting

  • Complex queries, large databases

  • Materialized view maintanence

CSCE 824 - Spring 2011


Logical integration

Logical Integration

  • No materialized global database

  • Virtual integration: data remains at the local (operational) databases

  • Global conceptual schema may not contain everything from local schemas

  • Autonomous and heterogeneous local systems

CSCE 824 - Spring 2011


Bottom up design

Bottom-Up Design

  • Global Conceptual Schema (GCS or mediated schema)

    • Defined first: local conceptual schemas (LCS) are mapped to GCS

    • Defined during the integration of the LCSs and develop the corresponding mappings from LCSs to the GCS

CSCE 824 - Spring 2011


Gcs defined first

GCS Defined First

  • Local-as-view (LAV) systems

    • Each LCS is treated as a view over the GCS

    • Query results: constrained to the objects in the local DBs while the GCS definition may be richer

    • Potential incomplete answers

  • Global-as-view GCS is defined as a set of views over the LCSs

    • View definition defines how to derive elements of the GCS

    • Query results: constrained to the GCS while the local DBs might be richer

CSCE 824 - Spring 2011


Design tasks

Design Tasks

  • Schema translation

  • Schema generation

  • Figure 4.3

CSCE 824 - Spring 2011


Intermediate canonical representation

Intermediate Canonical Representation

  • Expressive to incorporate all concepts in the local databases

  • Simple, intuitive, practical, etc.

  • Example: E/R model, relational model, graph/tree models, etc.

  • Tools

CSCE 824 - Spring 2011


Schema generation

Schema Generation

  • Schema matching: syntax and semantics

  • Integration of common schema elements

  • Schema mapping

  • See example 4.1, 4.2

CSCE 824 - Spring 2011


Schema matching

Schema Matching

  • Defined or discovered (e.g., web data)

  • Rules:

    • Correspondence between 2 elements

    • Predicate whether the correspondence holds or not

    • Similarity value between the 2 elements

CSCE 824 - Spring 2011


Finding correspondence

Finding Correspondence

  • Difficult process due to schema heterogeneity

  • Can be automated?

    • Insufficient schema and instance information

    • Unavailability of schema documentation

    • Subjectivity of matching

CSCE 824 - Spring 2011


Matching algorithm issues

Matching Algorithm Issues

  • Schema vs. instance matching

    • Concept match

    • Data instance: semantic inconsistencies

  • Element-level vs. structure-level mapping

    • Element name  semantics

    • Multiple attribute mapping?

  • Matching cardinality

    • One-to-one, one-to-many, many-to-many

CSCE 824 - Spring 2011


Semantic schema heterogeneity

Semantic Schema Heterogeneity

  • Semantic: meaning, interpretation, and intended use of data

    • Synonyms, homonyms, hypernyms

    • Different ontologies

    • Imprecise wording

CSCE 824 - Spring 2011


Distributed database management systems

Structural Schema Heterogeneity

  • Type conflict: attribute vs. entity

  • Dependency conflict: mapping cardinality inconsistencies

  • Key conflict: different primary keys

  • Behavioral conflict: modeling assumptions, e.g., referential integrity, deletion, etc.

Farkas

CSCE 824 - Spring 2011

22


Schema integration

Schema Integration

  • Binary

  • N-ary

CSCE 824 - Spring 2011


Schema mapping

Schema Mapping

  • How the data from local databases can be mapped to GCS

  • Mapping creating

  • Mapping maintanence

CSCE 824 - Spring 2011


Mapping creation

Mapping Creation

  • Input: LCS, GCS, M (schema matches)

  • Output: Q={Q1, …, Qk} such that

    • DBGCS =  Q(DBCLS)

CSCE 824 - Spring 2011


Security objectives

Security Objectives

  • Confidentiality

  • Integrity

  • Availability

CSCE 824 - Spring 2011


Question 1

Question 1

  • How distributed databases impact the security objectives?

    • Confidentiality in traditional vs. distributed DBs

    • Integrity in traditional vs. distributed DBs

    • Availability in traditional vs. distributed DBs

CSCE 824 - Spring 2011


Integrity

Integrity

  • Correctness criteria

    • Top-down design

    • Bottom-up design

CSCE 824 - Spring 2011


Availability

Availability

  • What are the issues related to availability when dealing with

    • Top-down design

    • Bottom-up design

CSCE 824 - Spring 2011


Confidentiality

Confidentiality

  • (will be covered in 2nd part of semester but…)

  • Centralized vs. distributed security policy

    • Top-down design

    • Bottom-up design

CSCE 824 - Spring 2011


Distributed database management systems

Next Class

Semantics-based Database Integration

CSCE 824 - Spring 2011


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