The key thing to remember is that in Spark RDD/DF are immutable. So once created you can not change them.
However there are many situation where you want the column type to be different.
E.g By default Spark comes with cars.csv where year column is a String. If you want to use a datetime function you need the column as a Datetime. You can change the column type from string to date in a new dataframe.
Here is an example to change the column type.
val df2 = sqlContext.load("com.databricks.spark.csv", Map("path" -> "file:///Users/vshukla/projects/spark/sql/core/src/test/resources/cars.csv", "header" -> "true"))
val df4 = df2.withColumn("year2", 'year.cast("Int")).select('year2 as 'year, 'make, 'model, 'comment)