Skip to main content

Managing Aging Data Using Persistent Views

  • Conference paper
Cooperative Information Systems (CoopIS 2000)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1901))

Included in the following conference series:

  • 476 Accesses

Abstract

Enabled by the continued advances in storage technologies, the amounts of on-line data grow at a rapidly increasing Pace. For example, this development is witnessed in the so-called data webhouses that accumulate data derived from clickstreams. The presence of very large and continuously growing amounts of data introduces new challenges, one of them being the need for effectively managing aging data that is perhaps inaccurate, partly outdated, and of reduced interest. This Paper describes a new mechanism, persistent views, that aids in flexibly reducing the volume of data, e.g., by enabling the replacement of such “low-interest ,” detailed data with aggregated data; and it outlines a strategy for implementing persistent views.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. Adiba, M.E., Lindsay, B.G.: Database Snapshots. In: Proc. VLDB, pp. 86–91 (1980)

    Google Scholar 

  2. Clifford, J., Dyreson, C., Isakowitz, T., Jensen, C.S., Snodgrass, R.T.: On the Semantics of “Now” in Databases. ACM TODS 22(2), 171–214 (1997)

    Article  Google Scholar 

  3. Garcia-Molina, H., Labio, W., Yang, J.: Expiring Data in a Warehouse. In: Proc. VLDB, pp. 500–511 (1998)

    Google Scholar 

  4. Gupta, A., Mumick, I.S. (eds.): Materialized Views—Techniques, Implementations, and Applications. The MIT Press, Cambridge (1999)

    Google Scholar 

  5. Klug, A.: Equivalence of Relational Algebra And Relational Calculus Query Languages Having Aggregate Functions. JACM 29(3), 699–717 (1982)

    Article  MATH  MathSciNet  Google Scholar 

  6. Snodgrass, R.T., Ahn, I.: Temporal databases. IEEE Computer 19(9), 35–42 (1986)

    Google Scholar 

  7. Skyt, J., Jensen, C.S.: Persistent Views—A Mechanism for Managing Aging Data. TR, Department of Computer Science, Aalborg University (March 2000)

    Google Scholar 

  8. Skyt, J., Jensen, C.S., Mark, L.: A Foundation for Vacuuming Temporal Databases (Manuscript under submission)

    Google Scholar 

  9. Widom, J.(eds.): Special Issue on Materialized Views and Data Warehousing. IEEE Data Engineering Bulletin 18(2) (June 1995)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2000 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Skyt, J., Jensen, C.S. (2000). Managing Aging Data Using Persistent Views. In: Scheuermann, P., Etzion, O. (eds) Cooperative Information Systems. CoopIS 2000. Lecture Notes in Computer Science, vol 1901. Springer, Berlin, Heidelberg. https://doi.org/10.1007/10722620_13

Download citation

  • DOI: https://doi.org/10.1007/10722620_13

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-41021-8

  • Online ISBN: 978-3-540-45266-9

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics