Not sure how to change your code because you'd need to generate the keys where
you get the data. Sorry about that.
I can tell you where to put the code to remap and sort though.
import org.apache.spark.rdd.OrderedRDDFunctions
val res2=reduced_hccg.map(_._2)
.map( x=> (newkey,x)).sortByKey(true) //and if you want remap them to remove
the key that you used for sorting: .map(x=> x._2)
res2.foreach(println)
val result= res2.mapPartitions(p=>{
val l=p.toList
val approx=new ListBuffer[(Int)]
val detail=new ListBuffer[Double]
for(i<-0 until l.length-1 by 2)
{
println(l(i),l(i+1))
approx+=(l(i),l(i+1))
}
approx.toList.iterator
detail.toList.iterator
})
result.foreach(println)
-----Original Message-----
From: yh18190 [mailto:yh18...@gmail.com]
Sent: March-28-14 5:17 PM
To: u...@spark.incubator.apache.org
Subject: RE: Splitting RDD and Grouping together to perform computation
Hi Andriana,
Thanks for suggestion.Could you please modify my code part where I need to do
so..I apologise for inconvinience ,becoz i am new to spark I coudnt apply
appropriately..i would be thankful to you.
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