Trouble with Scala pattern matching with map - required String - scala

Question

I'm trying to make my RDD into a pairdRDD, but having trouble with the pattern matching and I have no idea what I'm doing wrong..
val test = sc.textFile("neighborhood_test.csv");
val nhead0 = test.first;
val test_split = test.map(line => line.split("\t"));
val nhead = test_split.first;
val test_neigh0 = test.filter(line => line!= nhead0);
//test_neigh0.first = 3335 Dunlap Seattle
val test_neigh1 = test_neigh0.map(line => line.split("\t"));
//test_neigh1.first = Array[String] = Array(3335, Dunlap, Seattle)
val test_neigh = test_neigh1.map({case (id, neigh, city) => (id, (neigh, city))});
Gives error:
found : (T1, T2, T3)
required: String
val test_neigh = test_neigh0.map({case (id, neigh, city) => (id, (neigh, city))});
EDIT:
The inputfile is tab seperated and looks like this:
id neighbourhood city
3335 Dunlap Seattle
4291 Roosevelt Seattle
5682 South Delridge Seattle
As output I wan't a pairRDD with id as key, and (neigh, city) as value.

Answer 1

Neither test_neigh0.first nor test_neigh1.first is a triple, so you cannot pattern match it as such.
The elements in test_neigh1 are Array[String]. Under the assumption that these arrays are all of length 3, you can pattern match against them as { case Array(id, neigh, city) => ...}.
To make sure that you won't get a matching error if one of the line as more or less than 3 elements, you may collect on this pattern matching, instead of mapping on it.
val test_neigh: RDD[(String, (String, String))] = test_neigh1.collect{
case Array(id, neigh, city) => (id, (neigh, city))
}
EDIT
The issues you experienced as described in your comment are related to RDD[_] not being a usual collection (such as List, Array or Set). To avoid those, you might need to fetch elements in the array without pattern matching:
val test_neigh: RDD[(String, (String, String))] = test_neigh0.map(line => {
val arr = line.split("\t")
(arr(0), (arr(1), arr(2))
})

Answer 2

val baseRDD = sc.textFile("neighborhood_test.csv").filter { x => !x.contains("city") }
baseRDD.map { x =>
val split = x.split("\t")
(split(0), (split(1), split(2)))
}.groupByKey().foreach(println(_))
Result:
(3335,CompactBuffer((Dunlap,Seattle)))
(4291,CompactBuffer((Roosevelt,Seattle)))
(5682,CompactBuffer((South Delridge,Seattle)))