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Juliane Verwiebe

dblp:325/7351 · DBLP profile ↗
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2ranked-venue papers
2as first author
2since 2021 · last 2024
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Databases, data management, data science and information retrieval · 2 · 2 first-author · 2 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Databases, data mining, and information retrieval
1 paper
Data stream processing · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Data stream processing
window aggregation
0.712023
Survey of window types for aggregation in stream processing systems · VLDB J. 2023
Data stream processing
out-of-order stream processing
0.212023
Survey of window types for aggregation in stream processing systems · VLDB J. 2023
YearPublicationVenuePosition
2024 Correction to: Survey of window types for aggregation in stream processing systems
Juliane Verwiebe, Philipp M. Grulich, Jonas Traub, Volker Markl
VLDB J.1
2023 Survey of window types for aggregation in stream processing systems
abstract
Abstract In this paper, we present the first comprehensive survey of window types for stream processing systems which have been presented in research and commercial systems. We cover publications from the most relevant conferences, journals, and system whitepapers on stream processing, windowing, and window aggregation which have been published over the last 20 years. For each window type, we provide detailed specifications, formal notations, synonyms, and use-case examples. We classify each window type according to categories that have been proposed in literature and describe the out-of-order processing. In addition, we examine academic, commercial, and open-source systems with respect to the window types that they support. Our survey offers a comprehensive overview that may serve as a guideline for the development of stream processing systems, window aggregation techniques, and frameworks that support a variety of window types.
Juliane Verwiebe, Philipp M. Grulich, Jonas Traub, Volker Markl
VLDB J.1