Partitioned Auxiliary Views for Self-Maintainable Data Warehouses.

Mala Rajamani, Karen C. Davis: Partitioned Auxiliary Views for Self-Maintainable Data Warehouses. DOLAP 1998: 66-71

@inproceedings{DBLP:conf/dolap/RajamaniD98,
  author    = {Mala Rajamani and
               Karen C. Davis},
  title     = {Partitioned Auxiliary Views for Self-Maintainable Data Warehouses},
  booktitle = {DOLAP '98, ACM First International Workshop on Data Warehousing
               and OLAP, November 7, 1998, Bethesda, Maryland, USA, Proceedings},
  publisher = {ACM},
  year      = {1998},
  pages     = {66-71},
  ee        = {db/conf/dolap/RajamaniD98.html, http://doi.acm.org/10.1145/294260.294274},
  crossref  = {DBLP:conf/dolap/98},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}

Abstract

Recent research gives the minimal auxiliary data that has to be stored at a warehouse in order to make it self-maintainable, i.e., make it unnecessary for the warehouse to query a source for information when an update to the source is processed [6]. In this paper, we provide algorithms to partition the auxiliary views based on key and foreign key dependencies to obtain a reduction in storage. We prove that the auxiliary views can be reconstructed from our partitioned views, and thus the partitioned views are self-maintainable. We briefly discuss update costs and conclude that in partitioning and reducing auxiliary storage we decrease storage and modification costs, while the costs incurred for the insertion and deletion are increased in some cases.

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