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Storing and Querying Semantic Data in the Cloud

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Reasoning Web. Learning, Uncertainty, Streaming, and Scalability (Reasoning Web 2018)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11078))

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Abstract

In the last years, huge RDF graphs with trillions of triples were created. To be able to process this huge amount of data, scalable RDF stores are used, in which graph data is distributed over compute and storage nodes for scaling efforts of query processing and memory needs. The main challenges to be investigated for the development of such RDF stores in the cloud are: (i) strategies for data placement over compute and storage nodes, (ii) strategies for distributed query processing, and (iii) strategies for handling failure of compute and storage nodes. In this manuscript, we give an overview of how these challenges are addressed by scalable RDF stores in the cloud.

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Notes

  1. 1.

    https://spark.apache.org/.

  2. 2.

    https://hbase.apache.org/.

  3. 3.

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

  4. 4.

    http://titan.thinkaurelius.com/.

  5. 5.

    In the context of relational or NoSQL databases, graph covers are called sharding and the graph chunks shards. In the literature, there exist definitions of sharding that allow for data replication whereas others do not allow it.

  6. 6.

    We adapted the definition of an RDF molecule in [38] to allow for paths with a length \(\ge 1\).

  7. 7.

    The term anchor vertex was taken from [79].

  8. 8.

    \(\mathrm {dom}(\mu )\) refers to the set of variables of this binding.

  9. 9.

    \(\mu _{|_W}\) means that the domain of \(\mu \) is restricted to the variables in W.

  10. 10.

    https://aws.amazon.com/neptune/.

  11. 11.

    https://hadoop.apache.org/.

  12. 12.

    https://pig.apache.org/.

  13. 13.

    https://spark.apache.org/graphx/.

  14. 14.

    https://aws.amazon.com/de/dynamodb/.

  15. 15.

    https://cassandra.apache.org/.

  16. 16.

    https://accumulo.apache.org/.

  17. 17.

    https://impala.apache.org/.

  18. 18.

    https://www.couchbase.com/.

  19. 19.

    https://www.mongodb.com/.

  20. 20.

    http://lod-cloud.net/.

  21. 21.

    If the hash cover is only computed on the predicate, the resulting graph cover would be similar to the vertical graph split.

  22. 22.

    This idea is named differently in the literature. For instance, in Trinity.RDF [144] it is called graph exploration.

  23. 23.

    http://wifo5-03.informatik.uni-mannheim.de/bizer/berlinsparqlbenchmark/.

  24. 24.

    http://ldbcouncil.org/developer/spb.

  25. 25.

    https://graphql.org/.

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    Daniel Janke & Steffen Staab

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Janke, D., Staab, S. (2018). Storing and Querying Semantic Data in the Cloud. In: d’Amato, C., Theobald, M. (eds) Reasoning Web. Learning, Uncertainty, Streaming, and Scalability. Reasoning Web 2018. Lecture Notes in Computer Science(), vol 11078. Springer, Cham. https://doi.org/10.1007/978-3-030-00338-8_7

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