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Declarative and distributed graph analytics with GRADOOP

Google Scholar

Junghanns, Martin; Kießling, Max; Teichmann, Niklas; Gomez, Kevin; Petermann, Andre; Rahm, Erhard
Declarative and distributed graph analytics with GRADOOP
PVLDB
2018-08

Beschreibung

We demonstrate Gradoop, 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 sys-tem. Visitors of the demo can declare graph analytical pro-grams using the Gradoop operators and also visually expe-rience 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.