Use Spark API to build a decision tree classifier and train it on 80% of the samples and provide accuracy results using 20% of the samples. The Spark DataFrame (DF) has 10000 samples, four features (F1,F2,F3,F4), and the label has three classes ( 0,1,2) as given below. You can use Spark API website and Google Colab to develop your code