kmeans on spark error: requires number of clusters greater than one, but does not respond to changing 'k'

[kaileena1]

I have this code:

val fileName = """file:///home/user/data/csv/sessions_sample.csv"""
     val df = spark.read.format("csv").option("header", "true").option("inferSchema", "true").load(fileName)
     val input1 = df.select("id", "duration", "ip_dist", "txr1", "txr2", "txr3", "txr4").na.fill(3.0)
     val input2 = input1.map(r => (r.getInt(0), Vectors.dense((1 until r.size - 1).map{ i =>  r.getDouble(i)}.toArray[Double])))
     val input3 = input2.toDF("id", "features")
     input3.count()

val kmeans = new KMeans().setK(100).setSeed(1L).setFeaturesCol("features").setPredictionCol("prediction")
val model = kmeans.fit(input3)
val model = kmeans.fit(input3.select("features"))
// Make predictions
val predictions = model.transform(input3.select("features"))
val predictions = model.transform(input3)
val evaluator = new ClusteringEvaluator()
// i get error when i run this line
val silhouette = evaluator.evaluate(predictions)

Error: 

> java.lang.AssertionError: assertion failed: Number of clusters must be greater than one.
>   at scala.Predef$.assert(Predef.scala:170)
>   at org.apache.spark.ml.evaluation.SquaredEuclideanSilhouette$.computeSilhouetteScore(ClusteringEvaluator.scala:416)
>   at org.apache.spark.ml.evaluation.ClusteringEvaluator.evaluate(ClusteringEvaluator.scala:96)
>   ... 49 elided


Of course i tried changing k. It does not respond. On top of that, I have clusters with infinite cluster centers. For absolutely no value of k my clusters are stable => silhouette gives weird error?

`model.clusterCenters.foreach(println)`

> [3217567.1300936914,145.06533614203505,Infinity,Infinity,Infinity]


please advise.