Abstract
Derived data is maintained in a database system to correlate and summarize base data which record real world facts. As base data changes, derived data needs to be recomputed. A high performance system should execute all these updates and recomputations in a timely fashion so that the data remains fresh and useful, while at the same time executing user transactions quickly. This paper studies the intricate balance between recomputing derived data and transaction execution. Our focus is on efficient recomputation strategies — how and when recomputations should be done to reduce their cost without jeopardizing data timeliness. We propose the Forced Delay recomputation algorithm and show how it can exploit update locality to improve both data freshness and transaction response time.
This work was supported by the Telecommunications Center at Stanford University, by Hewlett Packard and by Philips. This work was also supported by an equipment grant from Digital Equipment Corporation.
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© 1996 Springer-Verlag Berlin Heidelberg
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Adelberg, B., Kao, B., Garcia-Molina, H. (1996). Database support for efficiently maintaining derived data. In: Apers, P., Bouzeghoub, M., Gardarin, G. (eds) Advances in Database Technology — EDBT '96. EDBT 1996. Lecture Notes in Computer Science, vol 1057. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0014155
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DOI: https://doi.org/10.1007/BFb0014155
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