package org.deeplearning4j.spark.data;

import org.apache.spark.api.java.JavaRDD;
import org.deeplearning4j.spark.BaseSparkTest;
import org.deeplearning4j.spark.util.SparkUtils;
import org.junit.Test;
import org.nd4j.linalg.api.ndarray.INDArray;
import org.nd4j.linalg.dataset.DataSet;
import org.nd4j.linalg.factory.Nd4j;

import java.util.ArrayList;
import java.util.Arrays;
import java.util.List;

import static org.junit.Assert.assertEquals;

/**
 * Created by Alex on 06/01/2017.
 */
public class TestShuffleExamples extends BaseSparkTest {

    @Test
    public void testShuffle(){
        List<DataSet> list = new ArrayList<>();
        for( int i=0; i<10; i++ ){
            INDArray f = Nd4j.valueArrayOf(new int[]{10,1}, i);
            INDArray l = f.dup();

            DataSet ds = new DataSet(f,l);
            list.add(ds);
        }

        JavaRDD<DataSet> rdd = sc.parallelize(list);

        JavaRDD<DataSet> shuffled = SparkUtils.shuffleExamples(rdd, 10, 10);

        List<DataSet> shuffledList = shuffled.collect();

        int totalExampleCount = 0;
        for(DataSet ds : shuffledList){
            totalExampleCount += ds.getFeatures().length();
            System.out.println(Arrays.toString(ds.getFeatures().data().asFloat()));

            assertEquals(ds.getFeatures(), ds.getLabels());
        }

        assertEquals(100, totalExampleCount);
    }

}

Add test for spark shuffling