Comparison of machine learning libraries used for classification
It's always good to see proper evalations and I am sure that this will provide food for thought and improvement for the tool owners.However - a couple of points.- One data set can't be more than an indicative test.
- Spark isn't designed for single machine environments.
- Spark isn't designed for "small problems" ie. where it takes 30 seconds to run the system. 
- If the algorithms are right then the results for accuracy should be identical. That they aren't indicates a bug, which would be worth unpicking with the relevant teams?