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Analyzing Temporal Graphs with Gradoop

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Abstract

The temporal analysis of evolving graphs is an important requirement in many domains but hardly supported in current graph database and graph processing systems. We therefore have started with extending the distributed graph analysis framework Gradoop for temporal graph analysis by adding time properties to vertices, edges and graphs and using them within graph operators. We outline these extensions and illustrate their use within analysis workflows. We further describe the implementation of the snapshot and diff operators and evaluated them.

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Notes

  1. https://flink.apache.org/

  2. https://neo4j.com/developer/cypher-query-language/

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Acknowledgements

This work is partially funded by the German Federal Ministry of Education and Research under grant BMBF 01IS18026B and by Sächsische Aufbau Bank (SAB) and the European Regional Development (EFRE) under grant No. 100302179.

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Authors and Affiliations

  1. University of Leipzig, Leipzig, Germany

    Christopher Rost & Erhard Rahm

  2. Leipzig University of Telecommunications, Leipzig, Germany

    Andreas Thor

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  1. Christopher Rost
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  2. Andreas Thor
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  3. Erhard Rahm
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Correspondence to Christopher Rost.

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Rost, C., Thor, A. & Rahm, E. Analyzing Temporal Graphs with Gradoop. Datenbank Spektrum 19, 199–208 (2019). https://doi.org/10.1007/s13222-019-00325-8

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  • DOI: https://doi.org/10.1007/s13222-019-00325-8

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