Load Balanced Query Evaluation in Shared-everything Environments (extended Version)


In this paper, we present data threaded execution, a new strategy to exploit pipelining and intra-operator parallelism in a shared-everything environment. Data threaded execution is very intuitive, straightforward to realize, and resistant against workload estimation errors and against the dis-cretization error of processor scheduling as it appears in conventional strategies. Furthermore, data threaded execution minimizes startup and shutdown execution delays. Simulation results show, that data threaded execution outperforms conventional strategies like segmented right-deep execution due to better utilization of parallel processing resources.

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@inproceedings{Manegold1996LoadBQ, title={Load Balanced Query Evaluation in Shared-everything Environments (extended Version)}, author={Stefan Manegold and Johann K. Obermaier and Florian Waas}, year={1996} }