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Hinode: implementing a vertex-centric modelling approach to maintaining historical graph data

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Abstract

Over the past few years, there has been a rapid increase of data originating from evolving networks such as social networks, sensor networks and others. A major challenge that arises when handling such networks and their respective graphs is the ability to issue a historical query on their data, that is, a query that is concerned with the state of the graph at previous time instances. While there has been a number of works that index the historical data in a time-centric manner (i.e. according to the time instance an update event occurs), in this work, we focus on the less-explored vertex-centric storage approach (i.e. according to the entity in which an update event occurs). We demonstrate that the design choices for a vertex-centric model are not trivial, by proposing two different modelling and storage models that leverage NoSQL technology and investigating their tradeoffs. More specifically, we experimentally evaluate the two models and show that under certain cases, their relative performance can differ by several times. Finally, we provide evidence that simple baseline and non-NoSQL solutions are slower by up to an order of magnitude.

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Notes

  1. Source code available at https://github.com/hinodeauthors/hinode.

  2. For reasons of clarity edge labels, vertex colors and edge weights are not shown.

  3. The queries executed were Average Vertex Degree, Degree Distribution and One-Hop Neighborhood Retrieval on the last snapshot of the sequence—see Sect. 5.1.

  4. citHep-Th SNAP Dataset [11]—see Sect. 5.1.

  5. Source code available at https://github.com/akosmato/HinodeNoSQL.

  6. Due to difficulties in assigning some specific edges to a particular snapshot we removed \(0.4\%\) of the total edges in the “hep-th” and “hep-ph” datasets and \(0.04\%\) edges of the “USPatents” dataset.

  7. As an example, a sequence of 100 snapshots that gets indexed every 20 snapshots would be comprised of five smaller ST indices whereas a vertex that exists in the first 75 snapshots would only be present in the first 4 smaller ST indices.

  8. e.g. A performance ratio of 2 corresponds to MT requiring half the execution time of ST.

  9. https://neo4j.com/.

  10. Measured through the “nodetool” utility.

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Authors and Affiliations

  1. Department of Informatics, Aristotle University of Thessaloniki, Thessaloníki, Greece

    Andreas Kosmatopoulos, Anastasios Gounaris & Kostas Tsichlas

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  1. Andreas Kosmatopoulos
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  2. Anastasios Gounaris
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  3. Kostas Tsichlas
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Correspondence to Andreas Kosmatopoulos.

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Kosmatopoulos, A., Gounaris, A. & Tsichlas, K. Hinode: implementing a vertex-centric modelling approach to maintaining historical graph data. Computing 101, 1885–1908 (2019). https://doi.org/10.1007/s00607-019-00715-6

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