javaapache-sparkk-meansapache-spark-mllib

Spark KMeans produces deterministic results and not random

I am running Spark KMeans and I would like to have random seeds in every run for different results every time, however this is not the case. This is the code that I am using:

KMeans kmeans = new KMeans().setK(4).setInitMode("random");
KMeansModel model = kmeans.fit(ds);
Dataset<Row> predictions = model.transform(ds);

I always get the same score and the same clusters. Am I missing something in the code?

Solution

  • I think you're missing the random seed:

    // Set the random seed
long seed = System.currentTimeMillis();

// Create the KMeans instance and set the random seed
KMeans kmeans = new KMeans().setK(4).setInitMode("random").setSeed(seed);
KMeansModel model = kmeans.fit(ds);
Dataset<Row> predictions = model.transform(ds);