The role of event-time order in data streaming analysis
Paper in proceeding, 2020
In contrast with traditional batch processing, data streaming applications require the user to reason about an additional dimension in the data: event-time. Numerous models have been proposed in the literature to reason about event-time, each with different guarantees and trade-offs. Since it is not always clear which of these models is appropriate for a particular application, this tutorial studies the relevant concepts and compares the available options. This study can be highly relevant for people working with data streaming applications, both researchers and industrial practitioners.
stream processing engines
data streaming
event-time
Author
Vincenzo Gulisano
Chalmers, Computer Science and Engineering (Chalmers), Networks and Systems (Chalmers)
Dimitrios Palyvos-Giannas
Chalmers, Computer Science and Engineering (Chalmers), Networks and Systems (Chalmers)
Bastian Havers
Chalmers, Computer Science and Engineering (Chalmers), Networks and Systems (Chalmers)
Marina Papatriantafilou
Chalmers, Computer Science and Engineering (Chalmers), Networks and Systems (Chalmers)
DEBS 2020 - Proceedings of the 14th ACM International Conference on Distributed and Event-Based Systems
214-217 3404088
978-145038028-7 (ISBN)
Montreal, Virtual, Canada,
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VINNOVA (2019-05884), 2020-03-12 -- 2022-12-31.
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Subject Categories
Other Computer and Information Science
Computer Systems
Areas of Advance
Information and Communication Technology
DOI
10.1145/3401025.3404088
ISBN
9781450380287
Related datasets
DOI: 10.1145/3401025.3404088 URI: https://dl.acm.org/doi/abs/10.1145/3401025.3404088