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The Poster "Generating Reproducible Out-of-Order Data Streams​" was Accepted at the DEBS '19 Conference

Philipp Grulich, Jonas Traub, Asterios Katsifodimos, Tilmann Rabl, Sebastian Breß and Volker Markl.
Generating Reproducible Out-of-Order Data Streams. 2019. In Proceedings of the 13th ACM International Conference on Distributed and Event-Based Systems​ (DEBS '19). ACM, Darmstadt​, Germany.

Abstract: 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, simulating arbitrary fractions of out-of-order tuples and their respective delays.​
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