Class

com.alpine.plugin.core.spark.templates

SparkDataFrameGUINode

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abstract class SparkDataFrameGUINode[Job <: SparkDataFrameJob] extends TemplatedSparkDataFrameGUINode[HdfsTabularDataset]

Control the GUI of your Spark job, through this you can specify any visualization for the output of your job, and what params the user will need to specify.

Linear Supertypes
TemplatedSparkDataFrameGUINode[HdfsTabularDataset], OperatorGUINode[HdfsTabularDataset, HdfsTabularDataset], AnyRef, Any
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  1. SparkDataFrameGUINode
  2. TemplatedSparkDataFrameGUINode
  3. OperatorGUINode
  4. AnyRef
  5. Any
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Instance Constructors

  1. new SparkDataFrameGUINode()

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Value Members

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

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    AnyRef → Any
  2. final def ##(): Int

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

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    AnyRef → Any
  4. final def asInstanceOf[T0]: T0

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    Any
  5. def clone(): AnyRef

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    Attributes
    protected[java.lang]
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    AnyRef
    Annotations
    @throws( ... )
  6. def defineEntireOutputSchema(inputSchema: TabularSchema, params: OperatorParameters): TabularSchema

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    Override this method to define an output schema in some way other than by defining an array of the fixed column definitions.

  7. def defineOutputSchemaColumns(inputSchema: TabularSchema, params: OperatorParameters): Seq[ColumnDef]

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    Override this method to define the output schema by assigning fixed column definitions.

    Override this method to define the output schema by assigning fixed column definitions. If you want to have a variable number of output columns, simply override the defineEntireOutputSchema method The default implementation of this method returns the same columns as the input data.

    inputSchema

    - the Alpine 'TabularSchema' for the input DataFrame

    params

    The parameters of the operator, including values set by the user.

    returns

    A list of Column definitions used to create the output schema

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

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  9. def equals(arg0: Any): Boolean

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  10. def finalize(): Unit

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    Attributes
    protected[java.lang]
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    Annotations
    @throws( classOf[java.lang.Throwable] )
  11. final def getClass(): Class[_]

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  12. def getOperatorStatus(context: OperatorDesignContext): OperatorStatus

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    Definition Classes
    OperatorGUINode
  13. def hashCode(): Int

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  14. final def isInstanceOf[T0]: Boolean

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

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  16. final def notify(): Unit

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  17. final def notifyAll(): Unit

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  18. def onInputOrParameterChange(inputSchemas: Map[String, TabularSchema], params: OperatorParameters, operatorSchemaManager: OperatorSchemaManager): OperatorStatus

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    Calls 'updateOutputSchema' when the parameters are changed

    Calls 'updateOutputSchema' when the parameters are changed

    Definition Classes
    SparkDataFrameGUINode → OperatorGUINode
  19. def onOutputVisualization(params: OperatorParameters, output: HdfsTabularDataset, visualFactory: VisualModelFactory): VisualModel

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    Definition Classes
    OperatorGUINode
  20. def onPlacement(operatorDialog: OperatorDialog, operatorDataSourceManager: OperatorDataSourceManager, operatorSchemaManager: OperatorSchemaManager): Unit

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    Defines the params the user will be able to select.

    Defines the params the user will be able to select. The default asks for desired output format & output location.

    Definition Classes
    SparkDataFrameGUINode → OperatorGUINode
  21. final def synchronized[T0](arg0: ⇒ T0): T0

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  22. def toString(): String

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  23. def updateOutputSchema(inputSchemas: Map[String, TabularSchema], params: OperatorParameters, operatorSchemaManager: OperatorSchemaManager): Unit

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    Attributes
    protected
  24. final def wait(): Unit

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    @throws( ... )
  25. final def wait(arg0: Long, arg1: Int): Unit

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    @throws( ... )
  26. final def wait(arg0: Long): Unit

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Inherited from TemplatedSparkDataFrameGUINode[HdfsTabularDataset]

Inherited from OperatorGUINode[HdfsTabularDataset, HdfsTabularDataset]

Inherited from AnyRef

Inherited from Any

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