Temporal View Self-Maintenance

  • Jun Yang
  • Jennifer Widom
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1777)


View self-maintenance refers to maintaining materialized views without accessing base data. Self-maintenance is particularly useful in data warehousing settings, where base data comes from sources that may be inaccessible. Self-maintenance has been studied for nontemporal views, but is even more important when a warehouse stores temporal views over the history of source data, since the source history needed to perform view maintenance may no longer exist. This paper tackles the self-maintenance problem for temporal views. We show how to derive auxiliary data to be stored at the warehouse so that the warehouse views and auxiliary data can be maintained without accessing the sources.

The temporal view self-maintenance problem is considerably harder than the nontemporal case because a temporal view may need to be maintained not only when source data is modified but also as time advances, and these two dimensions of change interact in subtle ways. We also seek to minimize the amount of auxiliary data required, taking into account different source capabilities and update constraints that are common in temporal warehousing scenarios. While our framework and algorithms are presented using a true temporal data model, our results apply directly to the ad-hoc temporal support (i.e., timestamp attributes in the standard relational model) commonly found in data warehouses today.


Time Advance Auxiliary Data Sale Department Original View Data Update 
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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    L. Bækgaard and L. Mark. Incremental computation of time-varying query expressions. IEEE Trans. on Knowledge and Data Engineering, 7(4):583–590, 1995.CrossRefGoogle Scholar
  2. 2.
    J. A. Blakeley, N. Coburn, and P.-Å. Larson. Updating derived relations: Detecting irrelevant and autonomously computable updates. ACM Trans. on Database Sys., 14(3):369–400, 1989.CrossRefMathSciNetGoogle Scholar
  3. 3.
    M. H. Böhlen, C. S. Jensen, and R. T. Snodgrass. Evaluating the completeness of TSQL2. In Proc. of the 1995 Intl. Workshop on Temporal Databases, pages 153–174, 1995.Google Scholar
  4. 4.
    J. Chomicki. Efficient checking of temporal integrity constraints using bounded history encoding. ACM Trans. on Database Sys., 20(2):148–186, 1995.Google Scholar
  5. 5.
    H. Garcia-Molina, W. J. Labio, and J. Yang. Expiring data in a warehouse. In Proc. of the 1998 Intl. Conf. on Very Large Data Bases, pages 500–511, 1998.Google Scholar
  6. 6.
    A. Gupta, H. V. Jagadish, and I. S. Mumick. Data integration using selfmaintainable views. In Proc. of the 1996 Intl. Conf. on Extending Database Technology, pages 140–144, 1996.Google Scholar
  7. 7.
    H. V. Jagadish, I. S. Mumick, and A. Silberschatz. View maintenance issues for the chronicle data model. In Proc. of the 1995 ACM Symp. on Principles of Database Sys., pages 113–124, 1995.Google Scholar
  8. 8.
    C. S. Jensen, M. D. Soo, and R. T. Snodgrass. Unifying temporal models via a conceptual model. Information Sys., 19(7):513–547, 1994.CrossRefGoogle Scholar
  9. 9.
    D. Quass, A. Gupta, I. S. Mumick, and J. Widom. Making views self-maintainable for data warehousing. In Proc. of the 1996 Intl. Conf. on Parallel and Distributed Information Sys., pages 158–169, 1996.Google Scholar
  10. 10.
    R. T. Snodgrass. The temporal query language TQuel. ACM Trans. on Database Sys., 12(2):247–298, 1987.CrossRefGoogle Scholar
  11. 11.
    J. Widom. Research problems in data warehousing. In Proc. of the 1995 Intl. Conf. on Information and Knowledge Management, pages 25–30, 1995.Google Scholar
  12. 12.
    J. Yang and J. Widom. Maintaining temporal views over non-temporal information sources for data warehousing. In Proc. of the 1998 Intl. Conf. on Extending Database Technology, pages 389–403, 1998.Google Scholar
  13. 13.
    J. Yang and J. Widom. Temporal view self-maintenance in a warehousing environment. Technical report, Computer Science Department, Stanford University, 1999.

Copyright information

© Springer-Verlag Berlin Heidelberg 2000

Authors and Affiliations

  • Jun Yang
    • 1
  • Jennifer Widom
    • 1
  1. 1.Computer Science DepartmentStanford UniversityUSA

Personalised recommendations