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Generating Reproducible Out-of-Order Data Streams
Zitatschl├╝ssel DBLP:conf/debs/GrulichTBKMR19
Autor Philipp M. Grulich, Jonas Traub, Sebastian Bress, Asterios Katsifodimos, Volker Markl, Tilmann Rabl
Jahr 2019
Journal DEBS
Zusammenfassung Evaluating modern stream processing systems in a reproducible manner requires data streams with different data distributions, data rates, and real-world characteristics such as delayed and out-of-order tuples. In this paper, we present an open source stream generator which generates reproducible and deterministic out-of-order streams based on real data files, simulating arbitrary fractions of out-of-order tuples and their respective delays.
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