case class DfTransformerWrapperDfsTransformer(transformer: ParsableDfTransformer, subFeedsToApply: Seq[String]) extends ParsableDfsTransformer with Product with Serializable
A Transformer to use single DataFrame Transformers as multiple DataFrame Transformers. This works by selecting the SubFeeds (DataFrames) the single DataFrame Transformer should be applied to. All other SubFeeds will be passed through without transformation.
- transformer
Configuration for a DfTransformer to be applied
- subFeedsToApply
Names of SubFeeds the transformation should be applied to.
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- ParsableDfsTransformer
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new
DfTransformerWrapperDfsTransformer(transformer: ParsableDfTransformer, subFeedsToApply: Seq[String])
- transformer
Configuration for a DfTransformer to be applied
- subFeedsToApply
Names of SubFeeds the transformation should be applied to.
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def
description: Option[String]
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- DfTransformerWrapperDfsTransformer → DfsTransformer
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def
factory: FromConfigFactory[ParsableDfsTransformer]
Returns the factory that can parse this type (that is, type
CO).Returns the factory that can parse this type (that is, type
CO).Typically, implementations of this method should return the companion object of the implementing class. The companion object in turn should implement FromConfigFactory.
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the factory (object) for this class.
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- DfTransformerWrapperDfsTransformer → ParsableFromConfig
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name: String
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notify(): Unit
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def
prepare(actionId: ActionId)(implicit context: ActionPipelineContext): Unit
Optional function to implement validations in prepare phase.
Optional function to implement validations in prepare phase.
- Definition Classes
- DfsTransformer
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- val subFeedsToApply: Seq[String]
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def
synchronized[T0](arg0: ⇒ T0): T0
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def
transform(actionId: ActionId, partitionValues: Seq[PartitionValues], dfs: Map[String, DataFrame])(implicit context: ActionPipelineContext): Map[String, DataFrame]
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
- Definition Classes
- DfTransformerWrapperDfsTransformer → DfsTransformer
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def
transformPartitionValues(actionId: ActionId, partitionValues: Seq[PartitionValues])(implicit context: ActionPipelineContext): Option[Map[PartitionValues, PartitionValues]]
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
- DfTransformerWrapperDfsTransformer → PartitionValueTransformer
- val transformer: ParsableDfTransformer
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