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Database Heterogeneity: Integration, Wrappers, and Mediators

Learn about database integration, wrappers, and mediators for dealing with the challenges of distribution, autonomy, and heterogeneity. Explore solutions and architecture for building applications using multiple databases.

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Database Heterogeneity: Integration, Wrappers, and Mediators

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  1. Lecture 13:Database HeterogeneityDebriefing Project Phase 2

  2. Outline • Database Integration • Wrappers • Mediators • Schema Integration Book Section

  3. Database Integration • How to build applications using multiple DBs? movie DB order movie order status Oracle IBM DB2 PointBase MySQL DVD orders amazon Ebay IMDB

  4. Problem Dimensions Distribution Autonomy Heterogeneity

  5. How to Deal with Distribution? • Problems • Solutions

  6. How to Deal with Autonomy? • Problems • Solutions

  7. How to Deal with Heterogeneity? • Problems • Solutions

  8. Solution Variants • General issues • Bottom-up vs. top-down engineering • Virtual vs. materialized integration • Read-only vs. read-write access • Transparency: language, schema, location • What did you do?

  9. A Generic System Architecture • Wrapper-Mediator architecture application 1 application 2 application 3 mediators integrate the data from the DBs mediator wrappers convert to acommon representation wrapper wrapper wrapper wrapper Oracle IBM DB2 PointBase MySQL DB4 DB1 DB2 DB3

  10. A Closer Look at Data Models • Data model used by sources • relational? HTML? XML? Text? • Data model used by integrated DB • canonical data model (e.g. relational, XML) • Query models • Structured queries, retrieval queries, data mining (statistics)

  11. A Generic Wrapper Architecture request/query result/data Compensation for missing processing capabilities Transformationof data model Metadata Communication interface integrity constraints Source data

  12. Wrapper Tasks • Data Model consists of • Data types • Integrity constraints • Operations (e.g. query language) • Translate among different data models • Overcome other "syntactic" heterogeneity Which was the task? How was it implemented?

  13. Example: Wrapping Relational Data in XML/HTML • Data types • trivial • Integrity Constraints (e.g. primary keys) • requires XML Schema • Operations • none in HTML Where did this play a role?

  14. Example: Wrapping XML/HTML into Relational • Data Types • which difficulties? • Integrity Constraints • none in HTML • Operations • requires generally XQuery • form fields can be considered as hard-coded queries

  15. A Closer Look at Schemas • Tight vs. loose integration • Is there a global schema? • Support for semantic integration • collection, fusion, abstraction

  16. Schema Architecture for Federated DBMS View 1 View 2 View 3 • accepted model for integrated database systems with integrated schema • 5-level architecture • data independence ... Integrated Schema Import Schema Import Schema Import Schema Import Schema Export Schema Export Schema Export Schema Export Schema Relational. DBMS Objectorient. DBMS Web Server File System

  17. Export Schema View 1 View 2 View 3 • provided by data source • source DB can change w/o changing export schema which was the export schema? ... Integrated Schema Import Schema Import Schema Import Schema Import Schema Export Schema Export Schema Export Schema Export Schema Relational. DBMS Objectorient. DBMS Web Server File System

  18. Import Schema View 1 View 2 View 3 • provided by wrapper • export schema can change w/o changing import schema which was the import schema? ... Integrated Schema Import Schema Import Schema Import Schema Import Schema Export Schema Export Schema Export Schema Export Schema Relational. DBMS Objectorient. DBMS Web Server File System

  19. Integrated Schema View 1 View 2 View 3 • provided by mediator • import schemas can change w/o changing integrated schema which was the integrated schema? ... Integrated Schema Import Schema Import Schema Import Schema Import Schema Export Schema Export Schema Export Schema Export Schema Relational. DBMS Objectorient. DBMS Web Server File System

  20. Application View View 1 View 2 View 3 • provided by application • integrated DB can change w/o changing application (code) which were application views? ... Integrated Schema Import Schema Import Schema Import Schema Import Schema Export Schema Export Schema Export Schema Export Schema Relational. DBMS Objectorient. DBMS Web Server File System

  21. Mediator Tasks • Integrate data with same "real-world meaning", but different representation • integration mapping  schema integration • can be implemented, e.g., as database view • Decompose queries against the integrated schema to queries against source DBs • only for virtual integration

  22. Correspondenceinvestigation Conflict resolutionand schema integration Schema Integration • Standard Methodology Schema translation(wrapper)

  23. Identifying Schema Correspondences Sources of information • source schema • source database • source application • database administrator, developer, user Which were your information sources?

  24. Identifying Schema Correspondences • Semantic correspondences • e.g. related names • Structural correspondences • reachability by paths • Data analysis • distribution of values Can you give examples?

  25. Conflicts • What types of problems did you encounter integrating corresponding data?

  26. Types of Conflicts • Schema level • Naming conflicts • Structural conflicts • Classification conflicts • Constraint and behavioral conflicts • Data level • Identification conflicts • Representational conflicts • Data errors

  27. Conflict Resolution • Depends on type of conflict • Requires construction of mappings • Mappings might be complex, e.g. not expressible as SQL views

  28. Naming Conflicts • Homonyms (give example) • same name used for different concepts • Resolution: introduce prefixes to distinguish the names • Synonyms (give example) • different names for the same concepts • Resolution: introduce a mapping to a common name

  29. Structural Conflicts • Different, non-corresponding attributes • Resolution: create a relation with the union of the attributes • Different datatypes • Resolution: build a mapping function • Different data model constructs • e.g. attribute vs. relation • Resolution: requires higher order mappings

  30. Classification Conflicts • Relations can have different coverage (inclusion, non-empty intersection) • Resolution: build generalization hierarchies • Additional problem • Identification of corresponding data instances • "real world" correspondence is application dependent

  31. Data Correspondences • Corresponding data instances • similar to naming conflicts at schema level • Resolution: mapping tables and functions • Similarity functions • Corresponding data values, data conflicts • of corresponding data instances • Resolution: mapping tables and functions • Prefer data from more trusted data source

  32. Constraint and Behavioral Conflicts • Cardinality conflicts • different types of cardinality constraints on relationships • Resolution: use the more general constraint • Behavioral conflicts for relation update • E.g. cascading delete vs. non-cascading • Resolution: add missing behavior at global level

  33. More? • Security • protecting data • Data Quality • actively managing data quality • Integration as Agreement Process • "emergent semantics"

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