Object

net.sansa_stack.inference.spark

RDFGraphMaterializer

Related Doc: package spark

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object RDFGraphMaterializer

The main entry class to compute the materialization on an RDF graph. Currently, only RDFS and OWL-Horst are supported.

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  1. case class Config(in: Seq[URI] = Seq(), out: URI = new URI("."), properties: Seq[Node] = Seq(), profile: ReasoningProfile = ReasoningProfile.RDFS, writeToSingleFile: Boolean = false, sortedOutput: Boolean = false, parallelism: Int = 4) extends Product with Serializable

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  1. final def !=(arg0: Any): Boolean

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  2. final def ##(): Int

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  3. final def ==(arg0: Any): Boolean

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  4. final def asInstanceOf[T0]: T0

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  5. def clone(): AnyRef

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  6. final def eq(arg0: AnyRef): Boolean

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  7. def equals(arg0: Any): Boolean

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  8. def finalize(): Unit

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  9. final def getClass(): Class[_]

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  10. def hashCode(): Int

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  11. final def isInstanceOf[T0]: Boolean

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  12. def main(args: Array[String]): Unit

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  13. final def ne(arg0: AnyRef): Boolean

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  14. implicit val nodeRead: Read[Node]

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  15. final def notify(): Unit

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  16. final def notifyAll(): Unit

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  17. val parser: OptionParser[Config]

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  18. implicit val profilesRead: Read[rules.ReasoningProfile.Value]

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  19. def run(input: Seq[URI], output: URI, profile: ReasoningProfile, properties: Seq[Node] = Seq(), writeToSingleFile: Boolean, sortedOutput: Boolean, parallelism: Int): Unit

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  20. final def synchronized[T0](arg0: ⇒ T0): T0

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  21. def toString(): String

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  22. final def wait(): Unit

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  23. final def wait(arg0: Long, arg1: Int): Unit

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  24. final def wait(arg0: Long): Unit

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