Error with RDD[Vector] in function parameter - scala

Question

I am trying to define a function in scala to iterate on it with Spark.
Here is my code :
import org.apache.spark.{SparkConf, SparkContext}
import org.apache.spark.sql.SQLContext
import org.apache.spark.ml.{Pipeline, PipelineModel}
import org.apache.spark.ml.clustering.KMeans
import org.apache.spark.mllib.linalg.Vectors
import org.apache.spark.ml.feature.VectorIndexer
import org.apache.spark.ml.feature.VectorAssembler
import org.apache.spark.rdd._
val assembler = new VectorAssembler()
.setInputCols(Array("feature1", "feature2", "feature3"))
.setOutputCol("features")
val assembled = assembler.transform(df)
// measures the average distance to centroid, for a model built with a given k.
def clusteringScore(data: RDD[Vector],k:Int) = {
val kmeans = new KMeans()
.setK(k)
.setFeaturesCol("features")
.setPredictionCol("prediction")
val model = kmeans.fit(data)
val WSSSE = model.computeCost(data) println(s"Within Set Sum of Squared Errors = $WSSSE")
}
(5 to 40 by 5).map(k => (k, clusteringScore(assembled, k))).
foreach(println)
With this code I get this error :
type Vector takes type parameters
I don't know what means this error...

Answer 1

You are not showing your imports, but you are probably importing Scala standard collections' Vector(this one takes a type parameter, e.g. Vector[Int]) instead of the SparkML Vector, which is a different type and you should import like this:
import org.apache.spark.mllib.linalg.Vector