See the explanation for Step by Step Solution and configuration.
Explanation:
Solution :
Step 1 : Create all three files in hdfs (We will do using Hue). However, you can first create in local filesystem and then upload it to hdfs.
Step 2 : Load EmployeeName.csv file from hdfs and create PairRDDs
val name = sc.textFile("spark5/EmployeeName.csv")
val namePairRDD = name.map(x=> (x.split(",")(0),x.split('V')(1)))
Step 3 : Load EmployeeSalary.csv file from hdfs and create PairRDDs
val salary = sc.textFile("spark5/EmployeeSalary.csv")
val salaryPairRDD = salary.map(x=> (x.split(",")(0),x.split(",")(1)))
Step 4 : Join all pairRDDS
val joined = namePairRDD.join(salaryPairRDD}
Step 5 : Remove key from RDD and Salary as a Key. val keyRemoved = joined.values
Step 6 : Now swap filtered RDD.
val swapped = keyRemoved.map(item => item.swap)
Step 7 : Now groupBy keys (It will generate key and value array) val grpByKey = swapped.groupByKey().collect()
Step 8 : Now create RDD for values collection
val rddByKey = grpByKey.map{case (k,v) => k->sc.makeRDD(v.toSeq)}
Step 9 : Save the output as a Text file.
rddByKey.foreach{ case (k,rdd) => rdd.saveAsTextFile("spark5/Employee"+k)}