K Means Clustering Explanation

[Matt Hicks]

I'm using K Means clustering for a project right now, and it's working very
well.  However, I'd like to determine from the clusters what information
distinctions define each cluster so I can explain the "reasons" data fits into a
specific cluster.
Is there a proper way to do this in Spark ML?