Bisecting K-means - training a clustering model

Training for bisecting K-means in Spark ML involves taking an approach similar to the other models -- we pass a DataFrame that contains our training data to the fit method of the KMeans object. Note that here we use the libsvm data format:

1. Instantiate the cluster object:

        val spConfig = (new                         
        SparkConf).setMaster("local[1]").setAppName("SparkApp"). 
        set("spark.driver.allowMultipleContexts", "true") 

        val spark = SparkSession 
          .builder() 
          .appName("Spark SQL Example") 
          .config(spConfig) 
          .getOrCreate() 

        val datasetUsers = spark.read.format("libsvm").load( 
          BASE + "/movie_lens_2f_users_libsvm/part-00000") 
        datasetUsers.show(3)

The output of the command show(3) is shown here:

         ...