Abstract
In this paper we propose adaptive data warehouse maintenance, based on the optimistic partial replication of base local computation at the view as well as communication with the outside sources, and lowers the execution load on the base sources, which leads to a more up-to-date state of the data warehouse view.
This work was supported in part by NSF under grant numbers CCR-9712108 and EIA-9818320 and IIS98-17432 and IIS99-70700.
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Stanoi, I., Agrawal, D., Abbadi, A.E. (2000). View Derivation Graph with Edge Fitting for Adaptive Data Warehousing. In: Kambayashi, Y., Mohania, M., Tjoa, A.M. (eds) Data Warehousing and Knowledge Discovery. DaWaK 2000. Lecture Notes in Computer Science, vol 1874. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44466-1_7
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DOI: https://doi.org/10.1007/3-540-44466-1_7
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