Spark MLlib has implemented the K-means clustering algorithm. The model training and prediction interfaces are similar to other machine learning algorithms. Let's see how it works by going through an example.
Let's use a sample data that has two dimensions: x and y. The plot of the points looks like the following screenshot:
From the preceding graph, we can see that four clusters form one solution. Let's try k = 2 and k=4. Let's see how the Spark clustering algorithm handles this Dataset and the groupings.
By now, we know very well how to load data using the read.csv() method. The following code file is ML03v2.scala:
We run the ML03v2 object:
The code to read data is very similar to the Regression and Classification examples. So we will skip it here; you can look at the source code anyway. After reading the data in, we have the Dataset with two columns: X and Y.
