Efficient Continuous Multi-Query Processing over Graph Streams

Eleftherios Zervakis, Vinay Setty, Christos Tryfonopoulos, Katja Hose

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

8 Citations (Scopus)
133 Downloads (Pure)


Graphs are ubiquitous and ever-present data structures that have a wide range of applications involving social networks, knowledge bases and biological interactions. The evolution of a graph in such scenarios can yield important insights about the nature and ac- tivities of the underlying network, which can then be utilized for applications such as news dissemination, network monitoring, and content curation. Capturing the continuous evolution of a graph can be achieved by long-standing sub-graph queries. Although, for many applications this can only be achieved by a set of quer- ies, state-of-the-art approaches focus on a single query scenario. In this paper, we therefore introduce the notion of continuous multi-query processing over graph streams and discuss its appli- cation to a number of use cases. To this end, we designed and developed a novel algorithmic solution for efficient multi-query evaluation against a stream of graph updates and experimentally demonstrated its applicability. Our results against two baseline approaches using real-world, as well as synthetic datasets, confirm a two orders of magnitude improvement of the proposed solution.
Original languageEnglish
Title of host publicationAdvances in Database Technology - EDBT 2020 : 23rd International Conference on Extending Database Technology, Proceedings
EditorsAngela Bonifati, Yongluan Zhou, Marcos Antonio Vaz Salles, Alexander Bohm, Dan Olteanu, George Fletcher, Arijit Khan, Bin Yang
Number of pages12
Publication date2020
ISBN (Electronic)978-3-89318-083-7
Publication statusPublished - 2020
Event23rd International Conference on Extending Database Technology, EDBT 2020 - Copenhagen, Denmark
Duration: 30 Mar 20202 Apr 2020


Conference23rd International Conference on Extending Database Technology, EDBT 2020
SeriesAdvances in Database Technology


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