Unable to perform aggregation on 2 values using groupByKey in spark using scala

3
votes

This question is regarding groupByKey() in spark using scala.

Consider below data

Name,marks,value
Chris,30,1
Chris,35,1
Robert,12,1
Robert,20,1

Created below rdd

val dataRDD = sc.parallelize(List(("Chris",30,1),("Chris",35,1),("Robert",12,1),("Robert",20,1)))

I am trying to create a key value pair of this like

val kvRDD = dataRDD.map(rec=> (rec._1, (rec._2,rec._3)))

Now I want sum of both the values. 

val sumRDD = kvRDD.groupByKey().map(rec => (rec._1,(rec._2._1.sum, rec._2._2.sum)))

However, I am facing below error.

<console>:28: error: value _2 is not a member of Iterable[(Int, Int)]

Can't we achieve the required using groupByKey?

3
scalaapache-sparkrdd

3 Answers

1
votes

Rather than groupByKey, I would suggest using the more efficient reduceByKey:

val dataRDD = sc.parallelize(Seq(
  ("Chris",30,1), ("Chris",35,1), ("Robert",12,1), ("Robert",20,1)
))

val kvRDD = dataRDD.map(rec => (rec._1, (rec._2, rec._3)))

val sumRDD = kvRDD.reduceByKey{ (acc, t) =>
  (acc._1 + t._1, acc._2 + t._2)
}

sumRDD.collect
// res1: Array[(String, (Int, Int))] = Array((Robert,(32,2)), (Chris,(65,2)))
1
votes

The value of kvRDD is array of tuple so you can sum array values directly, You can do like below

val sumRDD=kvRDD.groupByKey.map(rec=>(rec._1,(rec._2.map(_._1).sum,rec._2.map(_._2).sum)))

//Output
scala> sumRDD.collect
res11: Array[(String, (Int, Int))] = Array((Robert,(32,2)), (Chris,(65,2)))
1
votes

It is recommended to use reduceByKey in such scenario but still if you want to do it using groupByKey you can try the below approach. I am doing it python way you can try the same with scala.

 def summly(ilist):
        sum1=0
        sum2=0
        for i in ilist:
           sum1=sum1+i[0]
           sum2=sum2+i[1]
        return (sum1,sum2)

sumRDD = kvRDD.groupByKey().map(lambda x : (x[0],summly(list(x[1])))