Packages

class SparqlFrame extends Transformer

This SparqlFrame Transformer creates a dataframe based on a SPARQL query the resulting columns correspond to projection variables

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Transformer, PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
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  1. SparqlFrame
  2. Transformer
  3. PipelineStage
  4. Logging
  5. Params
  6. Serializable
  7. Serializable
  8. Identifiable
  9. AnyRef
  10. Any
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Instance Constructors

  1. new SparqlFrame()

Value Members

  1. final def !=(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  2. final def ##(): Int
    Definition Classes
    AnyRef → Any
  3. final def $[T](param: Param[T]): T
    Attributes
    protected
    Definition Classes
    Params
  4. final def ==(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  5. var _collapsByKey: Boolean
  6. var _featureDescriptions: Map[String, Map[String, Any]]
  7. var _keyColumnNameString: String
  8. var _query: String
  9. var _queryExcecutionEngine: query.spark.SPARQLEngine.Value
  10. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  11. final def clear(param: Param[_]): SparqlFrame.this.type
    Definition Classes
    Params
  12. def clone(): AnyRef
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native() @HotSpotIntrinsicCandidate()
  13. def collapsByKey(df: DataFrame): DataFrame

    SparqlFrame: The collapsByKey is set to true so we collaps the collumns by id column and als collect feature type information which are available in property .getFeatureTypes

    SparqlFrame: The collapsByKey is set to true so we collaps the collumns by id column and als collect feature type information which are available in property .getFeatureTypes

    df

    the input noncollapsed dataframe

    returns

    the collapsed dataframe

  14. def copy(extra: ParamMap): Transformer
    Definition Classes
    SparqlFrame → Transformer → PipelineStage → Params
  15. def copyValues[T <: Params](to: T, extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  16. final def defaultCopy[T <: Params](extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  17. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  18. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  19. def explainParam(param: Param[_]): String
    Definition Classes
    Params
  20. def explainParams(): String
    Definition Classes
    Params
  21. final def extractParamMap(): ParamMap
    Definition Classes
    Params
  22. final def extractParamMap(extra: ParamMap): ParamMap
    Definition Classes
    Params
  23. final def get[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  24. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native() @HotSpotIntrinsicCandidate()
  25. final def getDefault[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  26. def getFeatureDescriptions(): Map[String, Map[String, Any]]

    get the description of features after sparql extraction to decide over upcoming preprocessing strategies

    get the description of features after sparql extraction to decide over upcoming preprocessing strategies

    returns

    map representeing for each column some feature descriptions

  27. final def getOrDefault[T](param: Param[T]): T
    Definition Classes
    Params
  28. def getParam(paramName: String): Param[Any]
    Definition Classes
    Params
  29. def getSemanticTransformerDescription(): RDD[Triple]

    gain all inforamtion from this transformer as knowledge graph

    gain all inforamtion from this transformer as knowledge graph

    returns

    RDD[Trile] describing the meta information

  30. final def hasDefault[T](param: Param[T]): Boolean
    Definition Classes
    Params
  31. def hasParam(paramName: String): Boolean
    Definition Classes
    Params
  32. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native() @HotSpotIntrinsicCandidate()
  33. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  34. def initializeLogIfNecessary(isInterpreter: Boolean): Unit
    Attributes
    protected
    Definition Classes
    Logging
  35. final def isDefined(param: Param[_]): Boolean
    Definition Classes
    Params
  36. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  37. final def isSet(param: Param[_]): Boolean
    Definition Classes
    Params
  38. def isTraceEnabled(): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  39. def log: Logger
    Attributes
    protected
    Definition Classes
    Logging
  40. def logDebug(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  41. def logDebug(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  42. def logError(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  43. def logError(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  44. def logInfo(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  45. def logInfo(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  46. def logName: String
    Attributes
    protected
    Definition Classes
    Logging
  47. def logTrace(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  48. def logTrace(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  49. def logWarning(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  50. def logWarning(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  51. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  52. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native() @HotSpotIntrinsicCandidate()
  53. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native() @HotSpotIntrinsicCandidate()
  54. lazy val params: Array[Param[_]]
    Definition Classes
    Params
  55. final def set(paramPair: ParamPair[_]): SparqlFrame.this.type
    Attributes
    protected
    Definition Classes
    Params
  56. final def set(param: String, value: Any): SparqlFrame.this.type
    Attributes
    protected
    Definition Classes
    Params
  57. final def set[T](param: Param[T], value: T): SparqlFrame.this.type
    Definition Classes
    Params
  58. def setCollapsByKey(collapsByKey: Boolean): SparqlFrame.this.type

    Decide if we want to collaps the dataframe by an idea and collapse the samples so df consists of one row per entity

    Decide if we want to collaps the dataframe by an idea and collapse the samples so df consists of one row per entity

    collapsByKey

    if yes, it will be collapsed, default is false

    returns

    transformer itself

  59. def setCollapsColumnName(keyColumnNameString: String): SparqlFrame.this.type

    by which column to collapse if it shouldnt be first column

    by which column to collapse if it shouldnt be first column

    keyColumnNameString

    column name to collapse

    returns

    transformer itself

  60. final def setDefault(paramPairs: ParamPair[_]*): SparqlFrame.this.type
    Attributes
    protected
    Definition Classes
    Params
  61. final def setDefault[T](param: Param[T], value: T): SparqlFrame.this.type
    Attributes
    protected
    Definition Classes
    Params
  62. def setExperimentId(experimentURI: Node): SparqlFrame.this.type
  63. def setQueryExcecutionEngine(queryExcecutionEngine: query.spark.SPARQLEngine.Value): SparqlFrame.this.type

    setter to specify which query execution engine to be used

    setter to specify which query execution engine to be used

    option one is ontop option two sparqlify

    queryExcecutionEngine

    a string either ontop or sparqlify

    returns

    the set transformer

  64. def setSparqlQuery(queryString: String): SparqlFrame.this.type

    setter for query as string

    setter for query as string

    queryString

    a sparql query defining which features you want to have

    returns

    the set transformer

  65. val spark: SparkSession
    Attributes
    protected
  66. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  67. def toString(): String
    Definition Classes
    Identifiable → AnyRef → Any
  68. def transform(dataset: Dataset[_]): DataFrame

    creates a native spark Mllib DataFrame with columns corresponding to the projection variables

    creates a native spark Mllib DataFrame with columns corresponding to the projection variables

    columns are implicitly casted to string or if specified in literals to respective integer ect

    dataset

    the knowledge graph as dataset of jena triple

    returns

    a dataframe with columns corresponding to projection variables

    Definition Classes
    SparqlFrame → Transformer
  69. def transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" )
  70. def transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" ) @varargs()
  71. def transformSchema(schema: StructType): StructType
    Definition Classes
    SparqlFrame → PipelineStage
  72. def transformSchema(schema: StructType, logging: Boolean): StructType
    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()
  73. val uid: String
    Definition Classes
    SparqlFrame → Identifiable
  74. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  75. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  76. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Deprecated Value Members

  1. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] ) @Deprecated @deprecated
    Deprecated

    (Since version ) see corresponding Javadoc for more information.

Inherited from Transformer

Inherited from PipelineStage

Inherited from Logging

Inherited from Params

Inherited from Serializable

Inherited from Serializable

Inherited from Identifiable

Inherited from AnyRef

Inherited from Any

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