Reputation: 1883
Basically this question only for Scala.
How can I do the following transformation given an RDD with elements of the form
(List[String], String) => (String, String)
e.g.
([A,B,C], X)
([C,D,E], Y)
to
(A, X)
(B, X)
(C, X)
(C, Y)
(D, Y)
(E, Y)
So
Upvotes: 2
Views: 4034
Reputation: 645
Using beautiful for comprehensions and making the parameters generic
def convert[F, S](input: (List[F], S)): List[(F, S)] = {
for {
x <- input._1
} yield {
(x, input._2)
}
}
a sample call
convert(List(1, 2, 3), "A")
will give you
List((1,A), (2,A), (3,A))
Upvotes: 0
Reputation: 13346
With Spark you can solve your problem with:
object App {
def main(args: Array[String]) {
val input = Seq((List("A", "B", "C"), "X"), (List("C", "D", "E"), "Y"))
val conf = new SparkConf().setAppName("Simple Application").setMaster("local[4]")
val sc = new SparkContext(conf)
val rdd = sc.parallelize(input)
val result = rdd.flatMap {
case (list, label) => {
list.map( (_, label))
}
}
result.foreach(println)
}
}
This will output:
(C,Y)
(D,Y)
(A,X)
(B,X)
(E,Y)
(C,X)
Upvotes: 2
Reputation: 5424
val l = (List(1, 2, 3), "A")
val result = l._1.map((_, l._2))
println(result)
Will give you:
List((1,A), (2,A), (3,A))
Upvotes: 0
Reputation: 4510
I think that the RDD flatMapValues suits this case best.
val A = List((List(A,B,C),X),(List(A,B,C),Y))
val rdd = sc.parallelize(A)
val output = rdd.map(x=>(x._2,x._1)).flatMapValues(x=>x)
which will map X with every value in the List(A,B,C) resulting in RDD of pairs of RDD[(X,A),(X,B),(X,C)...(Y,A),(Y,B),(Y,C)]
Upvotes: 1
Reputation: 24802
scala> val l = List((List('a, 'b, 'c) -> 'x), List('c, 'd, 'e) -> 'y)
l: List[(List[Symbol], Symbol)] = List((List('a, 'b, 'c),'x),
(List('c, 'd, 'e),'y))
scala> l.flatMap { case (innerList, c) => innerList.map(_ -> c) }
res0: List[(Symbol, Symbol)] = List(('a,'x), ('b,'x), ('c,'x), ('c,'y),
('d,'y), ('e,'y))
Upvotes: 8