Propagation of Densities of Streaming Data within Query Graphs

Daum, Michael; Lauterwald, Frank; Baumgärtel, Philipp; Meyer-Wegener, Klaus

doi:10.1007/978-3-642-13818-8_40

Cited by 3 publications

(2 citation statements)

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“…In the second step, the evaluation of cost formulas provides an estimate for the operator graph's real processing costs. We already described an approach to support rate calculation by propagating the stream's attribute value distribution through the query graph to estimate selectivities [5].…”

Section: Applicationmentioning

confidence: 99%

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Black-box determination of cost models' parameters for federated stream-processing systems

Daum

Lauterwald

Baumgärtel

et al. 2011

Proceedings of the 15th Symposium on International Database Engineering &Amp; Applications - IDEAS '11

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For distribution and deployment of queries in distributed streamprocessing environments, it is vital to estimate the expected costs in advance. Having heterogeneous Stream-Processing Systems (SPSs) running on various hosts, the parameters of a cost model for an operator must be determined by measurements for each relevant combination of an SPS and hardware.This paper presents a black-box method that determines the parameters of appropriate cost models that regard system-specific behavior. For some SPSs, there might not be any appropriate cost model available due to the lack of internal knowledge. If no cost model is available for any reason, we provide and apply a nonparametric model.

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Section: Applicationmentioning

confidence: 99%

“…Hence the selectivity was 1/101. We already discussed density and selectivity estimation for non-uniform distributions in detail [5]. A simple model to estimate the processing costs of a tuple is based on the join's output rate.…”

Section: Joinmentioning

confidence: 99%