1 / 28

Computing Capabilities of Mediators

Computing Capabilities of Mediators. Ramana Yerneni Chen Li Hector Garcia-Molina Jeffrey Ullman. Wrapper Architecture. User Query. Catalog. Mediator. Wrapper. Wrapper. Data Source. Data Source. Data Source. Data Source. Scope. Framework for expressing source capabilities

norm
Download Presentation

Computing Capabilities of Mediators

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Computing Capabilities of Mediators Ramana Yerneni Chen Li Hector Garcia-Molina Jeffrey Ullman

  2. Wrapper Architecture User Query Catalog Mediator Wrapper Wrapper Data Source Data Source Data Source Data Source

  3. Scope • Framework for expressing source capabilities • Approach for computing mediator capabilities • Extending mediator capabilities

  4. Pathway • Capabilities of data sources • Simple mediators • Advanced techniques in mediators • Dynamic mediators • Concise capability description

  5. Capabilities of Data Sources • Attribute Adornments: • Adornment f : for free • Adornment u : for unspecifiable • Adornment b : for bound • Adornment c[s] : for compulsory constant • Adornment o[s] : for optional constant

  6. Capabilities of Data Sources R ( x1, Y, Z ) R ( X, Y, Z ) R(X Y Z) {b u f } R(X Y Z) {u b f } Exported Views Data Source

  7. Pathway • Capabilities of data sources • Simple mediators • Advanced techniques in mediators • Dynamic mediators • Concise capability description • Example

  8. Simple Mediators • Simple Mediator Properties • No post processing • Performs joins blindly • Union Views • Variable Adornments in Union View are computed from base view adornments • Mapping Function

  9. Simple Mediators Mapping Function:

  10. Simple Mediators • Union of two views • Example R(X, Y, Z) { b b u } Mediator Union View R(X, Y, Z) {b f u} Data Source R(X, Y, Z) {f b u} Data Source

  11. Simple Mediators • Union of two base views with multiple templates • Cross product of two template sets • For each pair apply mapping function • Union of multiple base views with multiple templates • Process two base views at a time • Repeat (n-1) times

  12. Simple Mediators • Join Views • Non-join attribute adornments are copied as they are in join view • Join attributes are computed using mapping function R1R2(X, Y, Z) { b b u } Mediator Join View R1(X,Y) {b f } Data Source R2(Y,Z) {b u} Data Source

  13. Simple Mediators • Selection Views • Pass the query to underlying data source as it is if it fits the template • Filter the results according to selection predicates • Projection Views • Hidden attributes are left unspecified • Works only if hidden attribute adornments are f, u, o

  14. Pathway • Capabilities of data sources • Simple mediators • Advanced techniques in mediators • Dynamic mediators • Concise capability description

  15. Advance Techniques in Mediators • Union Views • Post processing • Filter the input query to fit source views • Post process the results to match user requirements • Union view adornments are computed using Mapping function

  16. Advance Techniques in Mediators • Union View Example R(x1,y1,z1) R(X, Y, Z) { b u u } Mediator Union View { b f f } R(x1,Y,z1) R(x1,y1,Z) R(X,Y,Z){b f u } Data Source R(X,Y,Z){b u f } Data Source

  17. Advance Techniques in Mediators

  18. Advance Techniques in Mediators • Join Views • Non-join attribute adornments are copied as they are • Passing join attribute bindings from left to right view • Join attribute adornments are computed using mapping function

  19. Advance Techniques in Mediators • Join views: passing bindings R(x1,Z,V) R(X, Z, V) { b b f } Mediator Join View { b f f } R(z1,V) R(x1,Z) R1(X,Z){b f } Data Source R2(Z,V){b f } Data Source

  20. Pathway • Capabilities of data sources • Simple mediators • Advanced techniques in mediators • Dynamic mediators • Concise capability description

  21. Dynamic Mediators • Liberal templates • Answerability depends on state of data in data source • Can’t be always answered • Conservative templates • Can always be answered • Computed using techniques discussed in earlier slides

  22. Dynamic Mediators • Liberal Template Example R(x1,Y,Z) R(X, Y, Z) { b c[s] f } Mediator Join View { b f f } R(y1,Z) R1(x1,Y) R1(X,Y){b f } Data Source R2(Y,Z){c[s] f } Data Source

  23. Dynamic Mediators • Simple Mediators • Mediators employing advanced techniques • Post Processing • Passing bindings • Dynamic mediators • Liberal Templates

  24. Pathway • Capabilities of data sources • Simple mediators • Advanced techniques in mediators • Dynamic mediators • Concise capability description

  25. Concise Capability Description • Mediator view space is exponential • k templates per view, n sources • View space will be kn • Large number of templates are redundant • M1(b f b ) and M2(f f f ) : M2 is redundant

  26. Concise Capability Description • Adornment Graph f b O[s2] C[s1] u

  27. Concise Capability Description • Subsumption test • Template T subsumes T1 iff Every attribute x in T1 is atleast as restrictive as T • Subsumption test partitions the set of templates • Select the template which subsumes all other templates in a partition

  28. Pathway • Capabilities of data sources • Simple mediators • Advanced techniques in mediators • Dynamic mediators • Concise capability description

More Related