How to subsample windows of a DataSet in Spark?

Let's say I have a DataSet that look like this:

Name    | Grade
---------------
Josh    | 94
Josh    | 87
Amanda  | 96
Karen   | 78
Amanda  | 90
Josh    | 88

I would like to create a new DataSet where each name has 3 rows, where the additional rows (if any) are sampled from the ones of the same name (so Karen will have three identical rows, for example).

How do I do that without looping through each name?

Data preparation :

 val df = Seq(("Josh",94),("Josh",87),("Amanda",96),("Karen",78),("Amanda",90),("Josh",88)).toDF("Name","Grade")

Perform the following , only if your Data is skewed for a Name :
Add a random number, and filter the top 3 random numbers for each Name.

val df2 = df.withColumn("random", round(rand()*10))

import org.apache.spark.sql.expressions.Window
val windowSpec  = Window.partitionBy("Name").orderBy("random")

val df3 = df2.withColumn("row_number",row_number.over(windowSpec))
             .filter($"row_number" <= 3)

Now, aggregate the values for each Name and duplicate 3 times to ensure we have atleast 3 records for each Name. Then finally take 1st 3 values, and explode

df4.groupBy("Name").agg(collect_list("Grade") as "grade_list")
.withColumn("temp_list", slice( flatten(array_repeat($"grade_list", 3)), 1,3))
.select($"Name",explode($"temp_list") as "Grade").show

Notes :

• Since the above code will have max 3 values in grade_list , hence Duplicating it 3 times won't harm.
• Incase you don't use the Window step, you can have a combination of when( size($"grade_list") === n, ).otherwise() to above unnecessary duplication.