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The VLDB Journal

, Volume 13, Issue 3, pp 274–293 | Cite as

Preserving mapping consistency under schema changes

  • Yannis VelegrakisEmail author
  • Renée J. Miller
  • Lucian Popa
Article

Abstract.

In dynamic environments like the Web, data sources may change not only their data but also their schemas, their semantics, and their query capabilities. When a mapping is left inconsistent by a schema change, it has to be detected and updated. We present a novel framework and a tool (ToMAS) for automatically adapting (rewriting) mappings as schemas evolve. Our approach considers not only local changes to a schema but also changes that may affect and transform many components of a schema. Our algorithm detects mappings affected by structural or constraint changes and generates all the rewritings that are consistent with the semantics of the changed schemas. Our approach explicitly models mapping choices made by a user and maintains these choices, whenever possible, as the schemas and mappings evolve. When there is more than one candidate rewriting, the algorithm may rank them based on how close they are to the semantics of the existing mappings.

Keywords

Dynamic Environment Local Change Schema Change Mapping Consistency Constraint Change 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Abiteboul S, Duschka OM (1998) Complexity of answering queries using materialized views. In: PODS, pp 254-263Google Scholar
  2. 2.
    Bohannon P, Freire J, Haritsa JR, Ramanath M, Roy P, Siméon J (2002) LegoDB: Customizing relational storage for XML documents. In: VLDB, pp 1091-1094Google Scholar
  3. 3.
    Bertino E, Haas LM, Lindsay BG (1983) View management in distributed data base systems. In: VLDB, pp 376-378Google Scholar
  4. 4.
    Banerjee J, Kim W, Kim H, Korth HF (1987) Semantics and implementation of schema evolution in object-oriented databases. In: SIGMOD, pp 311-322Google Scholar
  5. 5.
    Bernstein P, Rahm E (2003) Data warehouse scenarios for model management. In: ER, pp 1-15Google Scholar
  6. 6.
    Claypool KT, Jin J, Rundensteiner EA (1998) SERF: Schema evolution through an extensible re-usable and flexible FRAMEWORK. In: CIKM, pp 314-321Google Scholar
  7. 7.
    Ceri S, Widom J (1991) Deriving production rules for incremental view maintenance. In: VLDB, pp 277-289Google Scholar
  8. 8.
    Florescu D, Kossmann D (1999) Storing and querying XML data using an RDMBS. IEEE Data Eng Bull 22(3):27-34Google Scholar
  9. 9.
    Fagin R, Kolaitis PG, Miller RJ, Popa L (2003) Data exchange: semantics and query answering. In: ICDT, pp 207-224Google Scholar
  10. 10.
    Fagin R, Kolaitis P, Popa L, Tan W (2004) Composing schema mappings: second-order dependencies to the rescue. In: PODSGoogle Scholar
  11. 11.
    Gyssens M, Lakshmanam L, Subramanian IN (1995) Tables as a paradigm for querying and restructuring. In: PODS, pp 93-103Google Scholar
  12. 12.
    Grahne G, Mendelzon AO (1999) Tableau techniques for querying information sources through global schemas. In: ICDT, pp 332-347Google Scholar
  13. 13.
    Gupta A, Mumick I, Ross K (1995) Adapting materialized views after redefinition. In: SIGMOD, pp 211-222Google Scholar
  14. 14.
    Halevy A, Ives Z, Suciu D, Tatarinov I (2003) Schema mediation in peer data management systems. In: ICDE, pp 505-517Google Scholar
  15. 15.
    Kantola M, Mannila H, Räihä K-J, Siirtola H (1992) Discovering functional and inclusion dependencies in relational databases. Int J Intell Sys 7(7):591-607zbMATHGoogle Scholar
  16. 16.
    Kotidis Y, Roussopoulos N (1999) DynaMat: a dynamic view management system for data warehouses. In: SIGMOD, pp 371-382Google Scholar
  17. 17.
    Kotidis Y, Roussopoulos N (2001) A case for dynamic view management. ACM Trans Database Sys 26(4):388-423CrossRefGoogle Scholar
  18. 18.
    Lenzerini M (2002) Data integration: a theoretical perspective. In: PODS, pp 233-246Google Scholar
  19. 19.
    Lerner BS (2000) A model for compound type changes encountered in schema evolution. ACM Trans Database Syst 25(1):83-127CrossRefGoogle Scholar
  20. 20.
    Lee AJ, Nica A, Rundensteiner EA (2002) The EVE approach: view synchronization in dynamic distributed environments. Trans Knowl Data Eng 14(5):931-954CrossRefGoogle Scholar
  21. 21.
    Levy AY, Rajaraman A, Ordille JJ (1996) Querying heterogeneous information sources using source descriptions. In: VLDB, pp 251-262Google Scholar
  22. 22.
    Madhavan J, Bernstein P, Rahm E (2001) Generic schema matching with Cupid. In: VLDB, pp 49-58Google Scholar
  23. 23.
    Mohania MK, Dong G (1996) Algorithms for adapting materialised views in data warehouses. In: CODAS, pp 309-316Google Scholar
  24. 24.
    Madhavan J, Halevy AY (2003) Composing mappings among data sources. In: VLDBGoogle Scholar
  25. 25.
    Miller RJ, Haas LM, Hernandez M (2003) Schema mapping as query discovery. In: VLDB, pp 77-88Google Scholar
  26. 26.
    Maier D, Mendelzon AO, Sagiv Y (1979) Testing implications of data dependencies. ACM Trans Database Syst 4(4):455-469CrossRefzbMATHGoogle Scholar
  27. 27.
    McBrien P, Poulovassilis A (2002) Schema evolution in heterogeneous database architectures, a schema transformation approach. In: CAiSE, pp 484-499Google Scholar
  28. 28.
    Mumick IS, Quass D, Mumick BS (1997) Maintenance of data cubes and summary tables in a warehouse. In: SIGMOD, pp 100-111Google Scholar
  29. 29.
    Melnik S, Rahm E, Bernstein P (2003) Rondo: a programming platform for generic model management. In: SIGMOD, pp 193-204Google Scholar
  30. 30.
    Popa L, Tannen V (1999) An equational chase for path-conjunctive queries, constraints, and views. In: ICDT, pp 39-57Google Scholar
  31. 31.
    Popa L, Velegrakis Y, Miller RJ, Hernandez MA, Fagin R (2002) Translating Web data. In: VLDB, pp 598-609Google Scholar
  32. 32.
    Rahm E, Bernstein PA (2001) A survey of approaches to automatic schema matching. VLDB J 10(4):334-350CrossRefGoogle Scholar
  33. 33.
    Spaccapietra S, Parent C (1994) View integration: a step forward in solving structural conflicts. Trans Knowl Data Eng 6(2):258-274CrossRefGoogle Scholar
  34. 34.
    Shamir R, Tsur D (1999) Faster subtree isomorphism. J Algorithms 33(2):267-280CrossRefMathSciNetzbMATHGoogle Scholar
  35. 35.
    Velegrakis Y (2004) Managing schema mappings in highly heterogeneous environments. PhD thesis, University of Toronto (in preparation)Google Scholar
  36. 36.
    Velegrakis Y, Miller RJ, Popa L (2003) Mapping adaptation under evolving schemas. In: VLDB, pp 584-595Google Scholar
  37. 37.
    Vassalos V, Papakonstantinou Y (1997) Describing and using query capabilities of heterogeneous sources. In: VLDB, pp 256-265Google Scholar
  38. 38.
    W3C (2001) XML Schema Part 0: Primer. http://www.w3.org/TR/xmlschema-0/, W3C RecommendationGoogle Scholar
  39. 39.
    Widom J (1995) Research problems in data warehousing. In: CIKM, pp 25-30Google Scholar

Copyright information

© Springer-Verlag Berlin/Heidelberg 2004

Authors and Affiliations

  • Yannis Velegrakis
    • 1
    Email author
  • Renée J. Miller
    • 1
  • Lucian Popa
    • 2
  1. 1.University of TorontoTorontoCanada
  2. 2.IBM Almaden Research CenterSan JoseUSA

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