trait CustomSnowparkDfTransformer extends Serializable
Interface to define a custom Snowpark-DataFrame transformation (1:1)
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def
transform(session: Session, options: Map[String, String], df: DataFrame, dataObjectId: String): DataFrame
Function to be implemented to define the transformation between an input and output DataFrame (1:1)
Function to be implemented to define the transformation between an input and output DataFrame (1:1)
- session
the Snowpark session
- options
Options specified in the configuration for this transformation
- df
DataFrames to be transformed
- dataObjectId
Id of DataObject of SubFeed
- returns
Transformed DataFrame
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def
transformPartitionValues(options: Map[String, String], partitionValues: Seq[PartitionValues]): 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.
- options
Options specified in the configuration for this transformation
- partitionValues
partition values to be transformed
- 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.
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