3. How can I start an HTTP SPARQL server?

1. How does SANSA perform distributed RDF querying?

SANSA uses vertical partitioning (VP) approach and is designed to support extensible partitioning of RDF data. Instead of dealing with a single three-column table (s, p, o), data is partitioned into multiple tables based on the used RDF predicates, RDF term types and literal datatypes. The first column of these tables is always a string representing the subject. The second column always represents the literal value as a Scala/Java datatype. Tables for storing literals with language tags have an additional third string column for the language tag.

  • The method for partitioning a RDD[Triple] is located in RdfPartitionUtilsSpark. It uses an RdfPartitioner which maps a Triple to a single RdfPartition instance.

    • RdfPartition, as the name suggests, represents a partition of the RDF data and defines two methods:
      • matches(Triple): Boolean: This method is used to test whether a triple fits into a partition.
      • Layout => TripleLayout: This method returns the TripleLayout associated with the partition, as explained below.
      • Furthermore,RdfPartitions are expected to be serializable, and to define equals and hash code.
    • TripleLayout instances are used to obtain framework-agnostic compact tabular representations of triples according to a partition. For this purpose it defines the two methods:
      • fromTriple(triple:Triple): Product: This method must, for a given triple, return its representation as a Product(this is the super class of all scalaTuples)
      • schema:Type: This method must return the exact scala type of the objects returned by fromTriple, such as typeOf[Tuple2[String,Double]]. Hence, layouts are expected to only yield instances of one specific type.

    See the available layouts for details.