spark官網給出的k-means的實現方式，原地址http://spark.apache.org/docs/latest/ml-clustering.html

package alg
import org.apache.spark.ml.clustering.KMeans
import org.apache.spark.ml.evaluation.ClusteringEvaluator
import org.apache.spark.sql.SparkSession
object k_means {

  def main(args:Array[String]):Unit={

    val spark:
 
 SparkSession = SparkSession.builder
      .appName("My")
      .master("local[*]")
      .getOrCreate()

    // Loads data.
    val dataset = spark.read.format("libsvm").load("data/mllib/sample_kmeans_data.txt")

    // Trains a k-means model.
    val kmeans = new KMeans().setK(2).setSeed(1L)
    val model =
 
 kmeans.fit(dataset)

    // Make predictions
    val predictions = model.transform(dataset)

    // Evaluate clustering by computing Silhouette score
    val evaluator = new ClusteringEvaluator()

    val silhouette = evaluator.evaluate(predictions)
    println(s"Silhouette with squared euclidean distance = $silhouette"
 
)

    // Shows the result.
    println("Cluster Centers: ")
    model.clusterCenters.foreach(println)
  }

}