Abstract
The barriers to parallel query execution are start-up time of parallel operations, interference and poor load balancing among the processors due to skewed data distribution. In this paper, we have described how these problems are addressed in DBS3, a shared-memory database system implemented on a 72-node KSR1 multiprocessor.
Our solution combines the advantages of static and dynamic partitioning. We use static partitioning of relations to reduce interference and dynamic allocation of processors to operations to reduce start-up time and improve load balancing. A major advantage of this solution is to be able to deal efficiently with skew by allowing each thread to dynamically choose which operation's instance it will execute. A performance analysis on our prototype with databases of the Wisconsin benchmark confirm these results. More information on this work can be found in http://rodin.inria.fr/bouganim.
This work has been partially funded by the CEC under ESPRIT project IDEA.
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© 1996 Springer-Verlag Berlin Heidelberg
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Bouganim, L., Dageville, B., Valduriez, P. (1996). Adaptive parallel query execution in DBS3. 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/BFb0014172
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DOI: https://doi.org/10.1007/BFb0014172
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