Add Column With Expression

It lets the user add a new column with an expression value of the desired data type.

This transformation needs below inputs from the user:

Input Arguments	Mandatory	Default Value	Description
column-name	Yes	-	Name of the new column to be added
column-expression	Yes	-	Expression for the value of the new column
column-data-type	No	-	The spark sql data type that new column needs to be casted
replace-existing	No	false	If set to true, if a column already exists with the same name as column-name, it will get replaced with the new value. If set to false, then it returns original dataframe.

User can configure the AddColumnWithExpression transformation in the below manner:

For example, consider we have below restonomer response in json:

{
  "col_A": "val_A",
  "col_B": "val_B",
  "col_C": 10.2
}

Now, if the requirement is to add a new column col_D with the value twice as the value of col_C, then user can configure the AddColumnWithExpression transformation in the below manner:

{
  type = "AddColumnWithExpression"
  column-name = "col_D"
  column-expression = "col_C * 2"
  replace-existing = true
}

The transformed response will now have the new column col_D added:

{
  "col_A": "val_A",
  "col_B": "val_B",
  "col_C": 10.2,
  "col_D": 20.4
}