sortByKey in Spark - scala

Question

New to Spark and Scala. Trying to sort a word counting example. My code is based on this simple example.
I want to sort the results alphabetically by key. If I add the key sort to an RDD:
val wordCounts = names.map((_, 1)).reduceByKey(_ + _).sortByKey()
then I get a compile error:
error: No implicit view available from java.io.Serializable => Ordered[java.io.Serializable].
[INFO] val wordCounts = names.map((_, 1)).reduceByKey(_ + _).sortByKey()
I don't know what the lack of an implicit view means. Can someone tell me how to fix it? I am running the Cloudera 5 Quickstart VM. I think it bundles Spark version 0.9.
Source of the Scala job
import org.apache.spark.SparkContext._
import org.apache.spark.SparkConf
object SparkWordCount {
def main(args: Array[String]) {
val sc = new SparkContext(new SparkConf().setAppName("Spark Count"))
val files = sc.textFile(args(0)).map(_.split(","))
def f(x:Array[String]) = {
if (x.length > 3)
x(3)
else
Array("NO NAME")
}
val names = files.map(f)
val wordCounts = names.map((_, 1)).reduceByKey(_ + _).sortByKey()
System.out.println(wordCounts.collect().mkString("\n"))
}
}
Some (unsorted) output
("INTERNATIONAL EYELETS INC",879)
("SHAQUITA SALLEY",865)
("PAZ DURIGA",791)
("TERESSA ALCARAZ",824)
("MING CHAIX",878)
("JACKSON SHIELDS YEISER",837)
("AUDRY HULLINGER",875)
("GABRIELLE MOLANDS",802)
("TAM TACKER",775)
("HYACINTH VITELA",837)

Answer 1

No implicit view means there is no scala function like this defined
implicit def SerializableToOrdered(x :java.io.Serializable) = new Ordered[java.io.Serializable](x) //note this function doesn't work
The reason this error is coming out is because in your function you are returning two different types with a super type of java.io.Serializable (ones a String the other an Array[String]). Also reduceByKey for obvious reasons requires the key to be an Orderable. Fix it like this
object SparkWordCount {
def main(args: Array[String]) {
val sc = new SparkContext(new SparkConf().setAppName("Spark Count"))
val files = sc.textFile(args(0)).map(_.split(","))
def f(x:Array[String]) = {
if (x.length > 3)
x(3)
else
"NO NAME"
}
val names = files.map(f)
val wordCounts = names.map((_, 1)).reduceByKey(_ + _).sortByKey()
System.out.println(wordCounts.collect().mkString("\n"))
}
}
Now the function just returns Strings instead of two different types