Declarative and distributed graph analytics with GRADOOP

We demonstrate G radoop , an open source framework that combines and extends features of graph database systems with the benefits of distributed graph processing. Using a rich graph data model and powerful graph operators, users can declaratively express graph analytical programs for distributed exe...

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Veröffentlicht in:Proceedings of the VLDB Endowment 2018-08, Vol.11 (12), p.2006-2009
Hauptverfasser: Junghanns, Martin, Kießling, Max, Teichmann, Niklas, Gómez, Kevin, Petermann, André, Rahm, Erhard
Format: Artikel
Sprache:eng
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Zusammenfassung:We demonstrate G radoop , an open source framework that combines and extends features of graph database systems with the benefits of distributed graph processing. Using a rich graph data model and powerful graph operators, users can declaratively express graph analytical programs for distributed execution without needing advanced programming experience or a deeper understanding of the underlying system. Visitors of the demo can declare graph analytical programs using the G radoop operators and also visually experience two of our advanced operators: graph pattern matching and graph grouping. We provide real world and artificial social network data with up to 10 billion edges and allow running the programs either locally or on a remote research cluster to demonstrate scalability.
ISSN:2150-8097
2150-8097
DOI:10.14778/3229863.3236246