Row Distributor

Create multiple DataFrames based on provided filter conditions from an input DataFrame.

This is useful for cases where rows from the input DataFrame needs to be distributed into multiple DataFrames in different ways for downstream Gems.

Parameters

Parameter	Description	Required
DataFrame	Input DataFrame for which rows needs to be distributed into multiple DataFrames	True
Filter Conditions	Boolean Type column or boolean expression for each output tab. Supports SQL, Python and Scala expressions	True

Example

info

Number of outputs can be changed as needed by clicking the + button.

Generated Code

Python

def RowDistributor(spark: SparkSession, in0: DataFrame) -> (DataFrame, DataFrame, DataFrame):
    df1 = in0.filter((col("order_status") == lit("Started")))
    df2 = in0.filter((col("order_status") == lit("Approved")))
    df3 = in0.filter((col("order_status") == lit("Finished")))

    return df1, df2, df3

Scala

object RowDistributor {

  def apply(
    spark: SparkSession,
    in:    DataFrame
  ): (DataFrame, DataFrame, DataFrame) =
    (in.filter(col("order_status") === lit("Started")),
     in.filter(col("order_status") === lit("Approved")),
     in.filter(col("order_status") === lit("Finished"))
    )

}