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net.sansa_stack.rdf.spark.stats

RDFStatistics

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object RDFStatistics extends Serializable

A Distributed implementation of RDF Statisctics.

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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. def AvgPerProperty(triples: RDD[Triple]): RDD[(Triple, Double)]

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    29.

    29. Average per property {int,float,time} criterion

    triples

    RDD of triples

    returns

    entities with their average values on the graph

  5. def AvgTypedStringLength(triples: RDD[Triple]): Double

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    22.

    22. Average typed string length criterion.

    triples

    RDD of triples

    returns

    the average typed string length used throughout the RDF graph.

  6. def AvgUntypedStringLength(triples: RDD[Triple]): Double

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    23.

    23. Average untyped string length criterion.

    triples

    RDD of triples

    returns

    the average untyped string length used throughout the RDF graph.

  7. def BlanksAsObject(triples: RDD[Triple]): RDD[Triple]

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    19.

    19. Blanks as object criterion

    triples

    RDD of triples

    returns

    number of triples where blanknodes are used as objects.

  8. def BlanksAsSubject(triples: RDD[Triple]): RDD[Triple]

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    18.

    18. Blanks as subject criterion

    triples

    RDD of triples

    returns

    number of triples where blanknodes are used as subjects.

  9. def ClassHierarchyDepth(triples: RDD[Triple]): VertexRDD[Int]

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    4.

    4. Class hierarchy depth criterion

    triples

    RDD of triples

    returns

    the depth of the graph

  10. def Datatypes(triples: RDD[Triple]): RDD[(String, Int)]

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    20.

    20. Datatypes criterion

    triples

    RDD of triples

    returns

    histogram of types used for literals.

  11. def EntitiesMentioned(triples: RDD[Triple]): Long

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    15.Entities mentioned criterion

    15.Entities mentioned criterion

    returns

    number of entities (resources / IRIs) that are mentioned within a RDF graph.

  12. def LabeledSubjects(triples: RDD[Triple]): RDD[Node]

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    24.

    24. Labeled subjects criterion.

    triples

    RDD of triples

    returns

    list of labeled subjects.

  13. def Languages(triples: RDD[Triple]): RDD[(String, Int)]

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    21.

    21. Languages criterion

    triples

    RDD of triples

    returns

    histogram of languages used for literals.

  14. def Links(triples: RDD[Triple]): RDD[(String, Int)]

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    26.

    26. Links criterion.

    triples

    RDD of triples

    returns

    list of namespaces and their frequentcies.

  15. def Literals(triples: RDD[Triple]): RDD[Triple]

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    * 17.

    * 17. Literals criterion

    triples

    RDD of triples

    returns

    number of triples that are referencing literals to subjects.

  16. def MaxPerProperty(triples: RDD[Triple]): (Triple, Int)

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    28.Maximum per property {int,float,time} criterion

    28.Maximum per property {int,float,time} criterion

    triples

    RDD of triples

    returns

    entities with their maximum values on the graph

  17. def PropertyHierarchyDepth(triples: RDD[Triple]): VertexRDD[Int]

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    12.

    12. Property hierarchy depth criterion

    triples

    RDD of triples

    returns

    the depth of the graph

  18. def PropertyUsageDistinctPerObject(triples: RDD[Triple]): RDD[(Iterable[Triple], Int)]

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    7.

    7. Property usage distinct per object criterion

    triples

    RDD of triples

    returns

    the usage of properties grouped by object

  19. def PropertyUsageDistinctPerSubject(triples: RDD[Triple]): RDD[(Iterable[Triple], Int)]

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    6.

    6. Property usage distinct per subject criterion

    triples

    RDD of triples

    returns

    the usage of properties grouped by subject

  20. def SameAs(triples: RDD[Triple]): RDD[Triple]

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    25.

    25. SameAs criterion.

    triples

    RDD of triples

    returns

    list of triples with owl#sameAs as predicate

  21. def SubclassUsage(triples: RDD[Triple]): Long

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    13.

    13. Subclass usage criterion

    triples

    RDD of triples

    returns

    the usage of subclasses on the given graph

  22. def Triples(triples: RDD[Triple]): Long

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    14.

    14. Triples criterion

    returns

    the amount of triples of a given graph.

  23. def TypedSubjects(triples: RDD[Triple]): RDD[Node]

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    24.

    24. Typed subjects criterion.

    triples

    RDD of triples

    returns

    list of typed subjects.

  24. final def asInstanceOf[T0]: T0

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  25. def clone(): AnyRef

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

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  27. def equals(arg0: Any): Boolean

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  28. def finalize(): Unit

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

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  30. def hashCode(): Int

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  31. final def isInstanceOf[T0]: Boolean

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

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  33. final def notify(): Unit

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  34. final def notifyAll(): Unit

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  35. def print(stats: RDD[String], source: String): Unit

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    Prints the Voidiy version of the given RDF dataset

    Prints the Voidiy version of the given RDF dataset

    stats

    given RDF dataset statistics

    source

    name of the Dataset:source--usualy the file's name

  36. def run(triples: RDD[Triple]): RDD[String]

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    Compute distributed RDF dataset statistics.

    Compute distributed RDF dataset statistics.

    triples

    RDF graph

    returns

    VoID description of the given dataset

  37. val spark: SparkSession

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

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  39. def toString(): String

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  40. def voidify(stats: RDD[String], source: String, output: String): Unit

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    Voidify RDF dataset based on the Vocabulary of Interlinked Datasets (VoID) https://www.w3.org/TR/void/

    Voidify RDF dataset based on the Vocabulary of Interlinked Datasets (VoID) https://www.w3.org/TR/void/

    stats

    given RDF dataset statistics

    source

    name of the Dataset:source--usualy the file's name

    output

    the directory to save RDF dataset summary

  41. final def wait(): Unit

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    @throws( ... )

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

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

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