Solution :

Step 1 : Create an RDD out of this list

val rdd = sc.parallelize(List( ("Deeapak" , "male", 4000}, ("Deepak" , "male", 2000), ("Deepika" , "female", 2000),("Deepak" , "female", 2000), ("Deepak" , "male", 1000} , ("Neeta" , "female", 2000}}}

Step 2 : Convert this RDD in pair RDD

val byKey = rdd.map({case (name,sex,cost) => (name,sex)->cost})

Step 3 : Now group by Key

val byKeyGrouped = byKey.groupByKey

Step 4 : Nowsum the cost for each group

val result = byKeyGrouped.map{case ((id1,id2),values) => (id1,id2,values.sum)}

Step 5 : Save the results result.repartition(1).saveAsTextFile("spark12/result.txt")