Poster: Generating Reproducible Out-of-Order Data Streams

Philipp M. Grulich, Jonas Traub, Sebastian Bress, Asterios Katsifodimos, Volker Markl, Tilmann Rabl

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

8 Citations (Scopus)
169 Downloads (Pure)

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.

Original languageEnglish
Title of host publicationDEBS 2019 - Proceedings of the 13th ACM International Conference on Distributed and Event-Based Systems
Subtitle of host publicationProceedings of the 13th ACM International Conference on Distributed and Event-Based Systems
Place of PublicationNew York
PublisherAssociation for Computing Machinery (ACM)
Pages256-257
Number of pages2
ISBN (Electronic)978-1-4503-6794-3
DOIs
Publication statusPublished - 24 Jun 2019
Event13th ACM International Conference on Distributed and Event-Based Systems, DEBS 2019 - Darmstadt, Germany
Duration: 24 Jun 201928 Jun 2019

Publication series

NameDEBS 2019 - Proceedings of the 13th ACM International Conference on Distributed and Event-Based Systems

Conference

Conference13th ACM International Conference on Distributed and Event-Based Systems, DEBS 2019
Country/TerritoryGermany
CityDarmstadt
Period24/06/1928/06/19

Keywords

  • Benchmarking
  • Data Generation
  • Out-of-Order
  • Stream Processing

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