Trait

io.smartdatalake.workflow.action.sparktransformer

DfsTransformer

Related Doc: package sparktransformer

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trait DfsTransformer extends PartitionValueTransformer

Interface to implement Spark-DataFrame transformers working with many inputs and many outputs (n:m)

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PartitionValueTransformer, AnyRef, Any
Known Subclasses
DfTransformerWrapperDfsTransformer, OptionsDfsTransformer, ParsableDfsTransformer, SQLDfsTransformer, ScalaClassDfsTransformer, ScalaCodeDfsTransformer
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Abstract Value Members

  1. abstract def description: Option[String]

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  2. abstract def name: String

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  3. abstract def transform(actionId: ActionId, partitionValues: Seq[PartitionValues], dfs: Map[String, DataFrame])(implicit session: SparkSession, context: ActionPipelineContext): Map[String, DataFrame]

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    Function to be implemented to define the transformation between many inputs and many outputs (n:m)

    Function to be implemented to define the transformation between many inputs and many outputs (n:m)

    actionId

    id of the action which executes this transformation. This is mainly used to prefix error messages.

    partitionValues

    partition values to transform

    dfs

    Map of (dataObjectId, DataFrame) tuples available as input

    returns

    Map of transformed (dataObjectId, DataFrame) tuples

Concrete Value Members

  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. final def ne(arg0: AnyRef): Boolean

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  13. final def notify(): Unit

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  14. final def notifyAll(): Unit

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  15. def prepare(actionId: ActionId)(implicit session: SparkSession, context: ActionPipelineContext): Unit

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    Optional function to implement validations in prepare phase.

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

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  17. def toString(): String

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  18. def transformPartitionValues(actionId: ActionId, partitionValues: Seq[PartitionValues])(implicit session: SparkSession, context: ActionPipelineContext): Option[Map[PartitionValues, PartitionValues]]

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    Optional function to define the transformation of input to output partition values.

    Optional function to define the transformation of input to output partition values. For example this enables to implement aggregations where multiple input partitions are combined into one output partition. Note that the default value is input = output partition values, which should be correct for most use cases.

    actionId

    id of the action which executes this transformation. This is mainly used to prefix error messages.

    partitionValues

    partition values to transform

    returns

    Map of input to output partition values. This allows to map partition values forward and backward, which is needed in execution modes. Return None if mapping is 1:1.

    Definition Classes
    PartitionValueTransformer

  19. final def wait(): Unit

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

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

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Inherited from PartitionValueTransformer

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