Open AccessProceedings Article
Expiring Data in a Warehouse
Hector Garcia-Molina,Wilburt Labio,Jun Yang +2 more
- pp 500-511
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A framework for incrementally removing warehouse data (without a need to fully recompute) is presented, and how the system should compensate when data is expired or other parameters changed is shown.Abstract:
Data warehouses collect data into materialized views for analysis. After some time, some of the data may no longer be needed or may not be of interest. In this paper, we handle this by expiring or removing unneeded materialized view tuples. A framework supporting such expiration is presented. Within it, a user or administrator can declaratively request expirations and can specify what type of modifications are expected from external sources. The latter can significantly increase the amount of data that can be expired. We present efficient algorithms for determining what data can be expired (data not needed for maintenance of other views), taking into account the types of updates that may occurread more
Citations
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Models and issues in data stream systems
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References
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Proceedings ArticleDOI
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Tomasz Imielinski,Witold Lipski +1 more
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Proceedings ArticleDOI
Maintaining views incrementally
TL;DR: A counting algorithm that tracks the number of alternative derivations (counts) for each derived tuple in a view, and shows that the count for a tuple can be computed at little or no cost above the cost of deriving the tuple.