com.alpine.plugin.core.spark.templates

InferredSparkDataFrameGUINode

abstract class InferredSparkDataFrameGUINode[Job <: InferredSparkDataFrameJob] extends SparkDataFrameGUINode[Job]

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. Uses the provided operator to generate an updated schema, this should work for most operators but if not (e.g. your operator doesn't handle empty data or output schema depends on input data) then you will have to perform your own schema update.

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

  1. new InferredSparkDataFrameGUINode()(implicit m: Manifest[Job])

Value Members

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

    Definition Classes
    AnyRef
  2. final def !=(arg0: Any): Boolean

    Definition Classes
    Any
  3. final def ##(): Int

    Definition Classes
    AnyRef → Any
  4. final def ==(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef
  5. final def ==(arg0: Any): Boolean

    Definition Classes
    Any
  6. final def asInstanceOf[T0]: T0

    Definition Classes
    Any
  7. def clone(): AnyRef

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

    Override this method to define an output schema instead of using automatic inference.

    Override this method to define an output schema instead of using automatic inference.

    Definition Classes
    InferredSparkDataFrameGUINode → SparkDataFrameGUINode
  9. def defineOutputSchemaColumns(inputSchema: TabularSchema, params: OperatorParameters): Seq[ColumnDef]

    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

    Definition Classes
    SparkDataFrameGUINode
  10. final def eq(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef
  11. def equals(arg0: Any): Boolean

    Definition Classes
    AnyRef → Any
  12. def finalize(): Unit

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

    Definition Classes
    AnyRef → Any
  14. def getOperatorStatus(context: OperatorDesignContext): OperatorStatus

    Definition Classes
    OperatorGUINode
  15. def hashCode(): Int

    Definition Classes
    AnyRef → Any
  16. final def isInstanceOf[T0]: Boolean

    Definition Classes
    Any
  17. lazy val localSqlContext: SQLContext

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

    Definition Classes
    AnyRef
  19. final def notify(): Unit

    Definition Classes
    AnyRef
  20. final def notifyAll(): Unit

    Definition Classes
    AnyRef
  21. def onInputOrParameterChange(inputSchemas: Map[String, TabularSchema], params: OperatorParameters, operatorSchemaManager: OperatorSchemaManager): OperatorStatus

    Calls 'updateOutputSchema' when the parameters are changed

    Calls 'updateOutputSchema' when the parameters are changed

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

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

    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
  24. lazy val sparkRuntimeUtils: SparkRuntimeUtils

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

    Definition Classes
    AnyRef
  26. def toString(): String

    Definition Classes
    AnyRef → Any
  27. def updateOutputSchema(inputSchemas: Map[String, TabularSchema], params: OperatorParameters, operatorSchemaManager: OperatorSchemaManager): Unit

    Attributes
    protected
    Definition Classes
    SparkDataFrameGUINode
  28. final def wait(): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  29. final def wait(arg0: Long, arg1: Int): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  30. final def wait(arg0: Long): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from SparkDataFrameGUINode[Job]

Inherited from TemplatedSparkDataFrameGUINode[HdfsTabularDataset]

Inherited from OperatorGUINode[HdfsTabularDataset, HdfsTabularDataset]

Inherited from AnyRef

Inherited from Any

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