Poster: Generating Reproducible Out-of-Order Data Streams

Conference Paper (2019)
Author(s)

Philipp M. Grulich (Technical University of Berlin)

Jonas Traub (DFKI GmbH, Technical University of Berlin)

Sebastian Bress (Technical University of Berlin, DFKI GmbH)

Asterios Katsifodimos (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Volker Markl (Technical University of Berlin, DFKI GmbH)

Tilmann Rabl (Hasso Plattner Institute)

Research Group
Web Information Systems
DOI related publication
https://doi.org/10.1145/3328905.3332511 Final published version
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Publication Year
2019
Language
English
Research Group
Web Information Systems
Pages (from-to)
256-257
ISBN (electronic)
978-1-4503-6794-3
Event
13th ACM International Conference on Distributed and Event-Based Systems, DEBS 2019 (2019-06-24 - 2019-06-28), Darmstadt, Germany
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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 based on real data files, simulating arbitrary fractions of out-of-order tuples and their respective delays.

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