main.java

import java.util.HashMap;
import scala.Tuple2;
import org.apache.spark.api.java.JavaPairRDD;
import org.apache.spark.api.java.JavaRDD;
import org.apache.spark.api.java.JavaSparkContext;
import org.apache.spark.api.java.function.Function;
import org.apache.spark.api.java.function.PairFunction;
import org.apache.spark.mllib.regression.LabeledPoint;
import org.apache.spark.mllib.tree.DecisionTree;
import org.apache.spark.mllib.tree.model.DecisionTreeModel;
import org.apache.spark.mllib.util.MLUtils;
import org.apache.spark.SparkConf;

public class main {

	public static void main2(String[] args) {
		// TODO Auto-generated method stub
		
		
		SparkConf sparkConf = new SparkConf().setAppName("JavaDecisionTree");
		JavaSparkContext sc = new JavaSparkContext(sparkConf);
		
		String datapath = "data/mllib/sample_libsvm_data.txt";
		JavaRDD<LabeledPoint> data = MLUtils.loadLibSVMFile(sc.sc(), datapath).toJavaRDD();
		// Split the data into training and test sets (30% held out for testing)
		JavaRDD<LabeledPoint>[] splits = data.randomSplit(new double[]{0.7, 0.3});
		JavaRDD<LabeledPoint> trainingData = splits[0];
		JavaRDD<LabeledPoint> testData = splits[1];

		
		
	}

}