Major Description
Now, the pyspark can only use withColumn to do column adding a column or replacing the existing column that has the same name. The scala withColumn can adding columns at one pass. [1]
Before this added, the user can only use withColumn again and again like:
self.df.withColumn("key1", col("key1")).withColumn("key2", col("key2")).withColumn("key3", col("key3"))
After the support, you user can use the with_columns complete batch operations:
self.df.withColumn(["key1", "key2", "key3"], [col("key1"), col("key2"), col("key3")])
