Efficient Continuous Multi-Query Processing over Graph Streams

Eleftherios Zervakis, Vinay Setty, Christos Tryfonopoulos, Katja Hose

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Abstrakt

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.
OriginalsprogEngelsk
TitelProceedings - The 23rd International Conference on Extending Database Technology (EDBT), March 30-April 2, 2020
ForlagAssociation for Computing Machinery
Publikationsdato2020
ISBN (Elektronisk)978-3-89318-083-7
DOI
StatusUdgivet - 2020

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Zervakis, E., Setty, V., Tryfonopoulos, C., & Hose, K. (2020). Efficient Continuous Multi-Query Processing over Graph Streams. I Proceedings - The 23rd International Conference on Extending Database Technology (EDBT), March 30-April 2, 2020 Association for Computing Machinery. https://doi.org/10.5441/002/edbt.2020.03