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An External Memory Algorithm for All-Pairs Regular Path Problem

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Database and Expert Systems Applications (Globe 2015, DEXA 2015)

Abstract

In this paper, we consider solving the all-pairs regular path problem on large graphs efficiently. Let G be a graph and r be a regular path query, and consider finding the answers of r on G. If G is so small that it fits in main memory, it suffices to load entire G into main memory and traverse G to find paths matching r. However, if G is too large and cannot fit in main memory, we need another approach. In this paper, we propose an external memory algorithm for solving all-pairs regular path problem on large graphs. Our algorithm finds the answers matching r by scanning the node list of G sequentially, which avoids random accesses to disk and thus makes regular path query processing I/O efficient.

Y. Kwon–Currently, the author is with Graduate School of Agricultural and Life Sciences, The University of Tokyo, 1-1-1 Yayoi, Bunkyo-ku, Tokyo 113-8657, Japan.

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Notes

  1. 1.

    http://www.sparsity-technologies.com/.

  2. 2.

    http://www.neo4j.org/.

  3. 3.

    https://github.com/tinkerpop/gremlin.

  4. 4.

    https://jena.apache.org/.

  5. 5.

    http://openrdf.org/.

  6. 6.

    We currently adopt breadth first search but any other search strategies can be applicable.

  7. 7.

    https://github.com/jexp/batch-import.

  8. 8.

    Neo4j has a declarative query language Cypher but it does not fully support regular path query. Thus we chose Gremlin in this experiment.

  9. 9.

    We also tried the same queries on Sparksee 5.1.0 and Apache Jena TDB, but obtained no result due to main memory exhaustion errors in both environments.

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Correspondence to Nobutaka Suzuki .

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Suzuki, N., Ikeda, K., Kwon, Y. (2015). An External Memory Algorithm for All-Pairs Regular Path Problem. In: Chen, Q., Hameurlain, A., Toumani, F., Wagner, R., Decker, H. (eds) Database and Expert Systems Applications. Globe DEXA 2015 2015. Lecture Notes in Computer Science(), vol 9262. Springer, Cham. https://doi.org/10.1007/978-3-319-22852-5_34

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  • DOI: https://doi.org/10.1007/978-3-319-22852-5_34

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