When using join in teradatamlspk, if join is of the following types: inner, cross, outer, full, fullouter, full_outer, left, leftouter, left_outer, right, rightouter, right_outer, and if both input DataFrames share common column names, then column names for those columns are prefixed with 'l' and 'r' in the output DataFrame.
Also the order of the columns varies.
PySpark
>>> df1.join(df, ["dept_name"]).show()
+---------+-------+-------+ |dept_name|dept_id|dept_id| +---------+-------+-------+ | Finance| 10| 10| | IT| 40| 40| |Marketing| 20| 20| | Sales| 30| 30| +---------+-------+-------+
teradatamlspk
>>> df1.join(df, ["dept_name"]).show()
+-----------+---------+---------+ |l_dept_name|l_dept_id|r_dept_id| +-----------+---------+---------+ | Sales| 30| 30| | IT| 40| 40| | Marketing| 20| 20| | Finance| 10| 10| +-----------+---------+---------+