src/test/java/org/apache/sysds/test/functions/aggregate/FullAggregateTest.java - systemds - Git at Google

 /*
  * Licensed to the Apache Software Foundation (ASF) under one
  * or more contributor license agreements.  See the NOTICE file
  * distributed with this work for additional information
  * regarding copyright ownership.  The ASF licenses this file
  * to you under the Apache License, Version 2.0 (the
  * "License"); you may not use this file except in compliance
  * with the License.  You may obtain a copy of the License at
  *
  *   http://www.apache.org/licenses/LICENSE-2.0
  *
  * Unless required by applicable law or agreed to in writing,
  * software distributed under the License is distributed on an
  * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
  * KIND, either express or implied.  See the License for the
  * specific language governing permissions and limitations
  * under the License.
  */

 package org.apache.sysds.test.functions.aggregate;

 import java.util.HashMap;

 import org.junit.AfterClass;
 import org.junit.Assert;
 import org.junit.BeforeClass;
 import org.junit.Test;
 import org.apache.sysds.api.DMLScript;
 import org.apache.sysds.common.Types.ExecMode;
 import org.apache.sysds.lops.LopProperties.ExecType;
 import org.apache.sysds.runtime.matrix.data.MatrixValue.CellIndex;
 import org.apache.sysds.test.AutomatedTestBase;
 import org.apache.sysds.test.TestConfiguration;
 import org.apache.sysds.test.TestUtils;
 import org.apache.sysds.utils.Statistics;

 /**
  *
  *
  */
 public class FullAggregateTest extends AutomatedTestBase
 {
 	private final static String TEST_NAME1 = "AllSum";
 	private final static String TEST_NAME2 = "AllMean";
 	private final static String TEST_NAME3 = "AllMax";
 	private final static String TEST_NAME4 = "AllMin";
 	private final static String TEST_NAME5 = "AllProd";
 	private final static String TEST_NAME6 = "DiagSum"; //trace

 	private final static String TEST_DIR = "functions/aggregate/";
 	private static final String TEST_CLASS_DIR = TEST_DIR + FullAggregateTest.class.getSimpleName() + "/";
 	private final static double eps = 1e-10;

 	private final static int rows1 = 1005;
 	private final static int cols1 = 1;
 	private final static int cols2 = 1079;
 	private final static double sparsity1 = 0.1;
 	private final static double sparsity2 = 0.7;

 	private enum OpType{
 		SUM,
 		MEAN,
 		MAX,
 		MIN,
 		PROD,
 		TRACE
 	}

 	@Override
 	public void setUp()
 	{
 		addTestConfiguration(TEST_NAME1, new TestConfiguration(TEST_CLASS_DIR, TEST_NAME1, new String[]{"B"}));
 		addTestConfiguration(TEST_NAME2, new TestConfiguration(TEST_CLASS_DIR, TEST_NAME2, new String[]{"B"}));
 		addTestConfiguration(TEST_NAME3, new TestConfiguration(TEST_CLASS_DIR, TEST_NAME3, new String[]{"B"}));
 		addTestConfiguration(TEST_NAME4, new TestConfiguration(TEST_CLASS_DIR, TEST_NAME4, new String[]{"B"}));
 		addTestConfiguration(TEST_NAME5, new TestConfiguration(TEST_CLASS_DIR, TEST_NAME5, new String[]{"B"}));
 		addTestConfiguration(TEST_NAME6, new TestConfiguration(TEST_CLASS_DIR, TEST_NAME6, new String[]{"B"}));

 		if (TEST_CACHE_ENABLED) {
 			setOutAndExpectedDeletionDisabled(true);
 		}
 	}

 	@BeforeClass
 	public static void init()
 	{
 		TestUtils.clearDirectory(TEST_DATA_DIR + TEST_CLASS_DIR);
 	}

 	@AfterClass
 	public static void cleanUp()
 	{
 		if (TEST_CACHE_ENABLED) {
 			TestUtils.clearDirectory(TEST_DATA_DIR + TEST_CLASS_DIR);
 		}
 	}

 	@Test
 	public void testSumDenseMatrixCP()
 	{
 		runColAggregateOperationTest(OpType.SUM, false, false, ExecType.CP);
 	}

 	@Test
 	public void testMeanDenseMatrixCP()
 	{
 		runColAggregateOperationTest(OpType.MEAN, false, false, ExecType.CP);
 	}

 	@Test
 	public void testMaxDenseMatrixCP()
 	{
 		runColAggregateOperationTest(OpType.MAX, false, false, ExecType.CP);
 	}

 	@Test
 	public void testMinDenseMatrixCP()
 	{
 		runColAggregateOperationTest(OpType.MIN, false, false, ExecType.CP);
 	}

 	@Test
 	public void testProdDenseMatrixCP()
 	{
 		runColAggregateOperationTest(OpType.PROD, false, false, ExecType.CP);
 	}

 	@Test
 	public void testTraceDenseMatrixCP()
 	{
 		runColAggregateOperationTest(OpType.TRACE, false, false, ExecType.CP);
 	}

 	@Test
 	public void testSumDenseVectorCP()
 	{
 		runColAggregateOperationTest(OpType.SUM, false, true, ExecType.CP);
 	}

 	@Test
 	public void testMeanDenseVectorCP()
 	{
 		runColAggregateOperationTest(OpType.MEAN, false, true, ExecType.CP);
 	}

 	@Test
 	public void testMaxDenseVectorCP()
 	{
 		runColAggregateOperationTest(OpType.MAX, false, true, ExecType.CP);
 	}

 	@Test
 	public void testMinDenseVectorCP()
 	{
 		runColAggregateOperationTest(OpType.MIN, false, true, ExecType.CP);
 	}

 	@Test
 	public void testProdDenseVectorCP()
 	{
 		runColAggregateOperationTest(OpType.PROD, false, true, ExecType.CP);
 	}

 	@Test
 	public void testTraceDenseVectorCP()
 	{
 		runColAggregateOperationTest(OpType.TRACE, false, true, ExecType.CP);
 	}

 	@Test
 	public void testSumSparseMatrixCP()
 	{
 		runColAggregateOperationTest(OpType.SUM, true, false, ExecType.CP);
 	}

 	@Test
 	public void testMeanSparseMatrixCP()
 	{
 		runColAggregateOperationTest(OpType.MEAN, true, false, ExecType.CP);
 	}

 	@Test
 	public void testMaxSparseMatrixCP()
 	{
 		runColAggregateOperationTest(OpType.MAX, true, false, ExecType.CP);
 	}

 	@Test
 	public void testMinSparseMatrixCP()
 	{
 		runColAggregateOperationTest(OpType.MIN, true, false, ExecType.CP);
 	}

 	@Test
 	public void testProdSparseMatrixCP()
 	{
 		runColAggregateOperationTest(OpType.PROD, true, false, ExecType.CP);
 	}

 	@Test
 	public void testTraceSparseMatrixCP()
 	{
 		runColAggregateOperationTest(OpType.TRACE, true, false, ExecType.CP);
 	}

 	@Test
 	public void testSumSparseVectorCP()
 	{
 		runColAggregateOperationTest(OpType.SUM, true, true, ExecType.CP);
 	}

 	@Test
 	public void testMeanSparseVectorCP()
 	{
 		runColAggregateOperationTest(OpType.MEAN, true, true, ExecType.CP);
 	}

 	@Test
 	public void testMaxSparseVectorCP()
 	{
 		runColAggregateOperationTest(OpType.MAX, true, true, ExecType.CP);
 	}

 	@Test
 	public void testMinSparseVectorCP()
 	{
 		runColAggregateOperationTest(OpType.MIN, true, true, ExecType.CP);
 	}

 	@Test
 	public void testProdSparseVectorCP()
 	{
 		runColAggregateOperationTest(OpType.PROD, true, true, ExecType.CP);
 	}

 	@Test
 	public void testTraceSparseVectorCP()
 	{
 		runColAggregateOperationTest(OpType.TRACE, true, true, ExecType.CP);
 	}

 	@Test
 	public void testSumDenseMatrixSP()
 	{
 		runColAggregateOperationTest(OpType.SUM, false, false, ExecType.SPARK);
 	}

 	@Test
 	public void testMeanDenseMatrixSP()
 	{
 		runColAggregateOperationTest(OpType.MEAN, false, false, ExecType.SPARK);
 	}

 	@Test
 	public void testMaxDenseMatrixSP()
 	{
 		runColAggregateOperationTest(OpType.MAX, false, false, ExecType.SPARK);
 	}

 	@Test
 	public void testMinDenseMatrixSP()
 	{
 		runColAggregateOperationTest(OpType.MIN, false, false, ExecType.SPARK);
 	}

 	@Test
 	public void testProdDenseMatrixSP()
 	{
 		runColAggregateOperationTest(OpType.PROD, false, false, ExecType.SPARK);
 	}

 	@Test
 	public void testTraceDenseMatrixSP()
 	{
 		runColAggregateOperationTest(OpType.TRACE, false, false, ExecType.SPARK);
 	}

 	@Test
 	public void testSumDenseVectorSP()
 	{
 		runColAggregateOperationTest(OpType.SUM, false, true, ExecType.SPARK);
 	}

 	@Test
 	public void testMeanDenseVectorSP()
 	{
 		runColAggregateOperationTest(OpType.MEAN, false, true, ExecType.SPARK);
 	}

 	@Test
 	public void testMaxDenseVectorSP()
 	{
 		runColAggregateOperationTest(OpType.MAX, false, true, ExecType.SPARK);
 	}

 	@Test
 	public void testMinDenseVectorSP()
 	{
 		runColAggregateOperationTest(OpType.MIN, false, true, ExecType.SPARK);
 	}

 	@Test
 	public void testProdDenseVectorSP()
 	{
 		runColAggregateOperationTest(OpType.PROD, false, true, ExecType.SPARK);
 	}

 	@Test
 	public void testTraceDenseVectorSP()
 	{
 		runColAggregateOperationTest(OpType.TRACE, false, true, ExecType.SPARK);
 	}

 	@Test
 	public void testSumSparseMatrixSP()
 	{
 		runColAggregateOperationTest(OpType.SUM, true, false, ExecType.SPARK);
 	}

 	@Test
 	public void testMeanSparseMatrixSP()
 	{
 		runColAggregateOperationTest(OpType.MEAN, true, false, ExecType.SPARK);
 	}

 	@Test
 	public void testMaxSparseMatrixSP()
 	{
 		runColAggregateOperationTest(OpType.MAX, true, false, ExecType.SPARK);
 	}

 	@Test
 	public void testMinSparseMatrixSP()
 	{
 		runColAggregateOperationTest(OpType.MIN, true, false, ExecType.SPARK);
 	}

 	@Test
 	public void testProdSparseMatrixSP()
 	{
 		runColAggregateOperationTest(OpType.PROD, true, false, ExecType.SPARK);
 	}

 	@Test
 	public void testTraceSparseMatrixSP()
 	{
 		runColAggregateOperationTest(OpType.TRACE, true, false, ExecType.SPARK);
 	}

 	@Test
 	public void testSumSparseVectorSP()
 	{
 		runColAggregateOperationTest(OpType.SUM, true, true, ExecType.SPARK);
 	}

 	@Test
 	public void testMeanSparseVectorSP()
 	{
 		runColAggregateOperationTest(OpType.MEAN, true, true, ExecType.SPARK);
 	}

 	@Test
 	public void testMaxSparseVectorSP()
 	{
 		runColAggregateOperationTest(OpType.MAX, true, true, ExecType.SPARK);
 	}

 	@Test
 	public void testMinSparseVectorSP()
 	{
 		runColAggregateOperationTest(OpType.MIN, true, true, ExecType.SPARK);
 	}

 	@Test
 	public void testProdSparseVectorSP()
 	{
 		runColAggregateOperationTest(OpType.PROD, true, true, ExecType.SPARK);
 	}

 	@Test
 	public void testTraceSparseVectorSP()
 	{
 		runColAggregateOperationTest(OpType.TRACE, true, true, ExecType.SPARK);
 	}

 	private void runColAggregateOperationTest( OpType type, boolean sparse, boolean vector, ExecType instType)
 	{
 		ExecMode platformOld = rtplatform;
 		switch( instType ){
 			case SPARK: rtplatform = ExecMode.SPARK; break;
 			default: rtplatform = ExecMode.HYBRID; break;
 		}

 		boolean sparkConfigOld = DMLScript.USE_LOCAL_SPARK_CONFIG;
 		if( rtplatform == ExecMode.SPARK )
 			DMLScript.USE_LOCAL_SPARK_CONFIG = true;

 		try
 		{
 			String TEST_NAME = null;
 			switch( type )
 			{
 				case SUM: TEST_NAME = TEST_NAME1; break;
 				case MEAN: TEST_NAME = TEST_NAME2; break;
 				case MAX: TEST_NAME = TEST_NAME3; break;
 				case MIN: TEST_NAME = TEST_NAME4; break;
 				case PROD: TEST_NAME = TEST_NAME5; break;
 				case TRACE: TEST_NAME = TEST_NAME6; break;
 			}

 			int cols = (vector) ? cols1 : cols2;
 			int rows = (type==OpType.TRACE) ? cols : rows1;
 			double sparsity = (sparse) ? sparsity1 : sparsity2;

 			String TEST_CACHE_DIR = "";
 			if (TEST_CACHE_ENABLED)
 			{
 				TEST_CACHE_DIR = type.ordinal() + "_" + rows + "_" + cols + "_" + sparsity + "/";
 			}

 			TestConfiguration config = getTestConfiguration(TEST_NAME);
 			loadTestConfiguration(config, TEST_CACHE_DIR);

 			/* This is for running the junit test the new way, i.e., construct the arguments directly */
 			String HOME = SCRIPT_DIR + TEST_DIR;
 			fullDMLScriptName = HOME + TEST_NAME + ".dml";
 			programArgs = new String[]{"-args", input("A"),
 				Integer.toString(rows), Integer.toString(cols), output("B") };

 			fullRScriptName = HOME + TEST_NAME + ".R";
 			rCmd = "Rscript" + " " + fullRScriptName + " " + inputDir() + " " + expectedDir();

 			//generate actual dataset
 			double[][] A = getRandomMatrix(rows, cols, -0.05, 1, sparsity, 7);
 			writeInputMatrix("A", A, true);

 			runTest(true, false, null, -1);
 			if( instType==ExecType.CP ) //in CP no MR jobs should be executed
 				Assert.assertEquals("Unexpected number of executed MR jobs.", 0, Statistics.getNoOfExecutedSPInst());

 			runRScript(true);

 			//compare matrices
 			HashMap<CellIndex, Double> dmlfile = readDMLMatrixFromOutputDir("B");
 			HashMap<CellIndex, Double> rfile  = readRMatrixFromExpectedDir("B");
 			TestUtils.compareMatrices(dmlfile, rfile, eps, "Stat-DML", "Stat-R");
 		}
 		finally
 		{
 			rtplatform = platformOld;
 			DMLScript.USE_LOCAL_SPARK_CONFIG = sparkConfigOld;
 		}
 	}
 }
	/*
	* Licensed to the Apache Software Foundation (ASF) under one
	* or more contributor license agreements. See the NOTICE file
	* distributed with this work for additional information
	* regarding copyright ownership. The ASF licenses this file
	* to you under the Apache License, Version 2.0 (the
	* "License"); you may not use this file except in compliance
	* with the License. You may obtain a copy of the License at
	*
	* http://www.apache.org/licenses/LICENSE-2.0
	*
	* Unless required by applicable law or agreed to in writing,
	* software distributed under the License is distributed on an
	* "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
	* KIND, either express or implied. See the License for the
	* specific language governing permissions and limitations
	* under the License.
	*/

	package org.apache.sysds.test.functions.aggregate;

	import java.util.HashMap;

	import org.junit.AfterClass;
	import org.junit.Assert;
	import org.junit.BeforeClass;
	import org.junit.Test;
	import org.apache.sysds.api.DMLScript;
	import org.apache.sysds.common.Types.ExecMode;
	import org.apache.sysds.lops.LopProperties.ExecType;
	import org.apache.sysds.runtime.matrix.data.MatrixValue.CellIndex;
	import org.apache.sysds.test.AutomatedTestBase;
	import org.apache.sysds.test.TestConfiguration;
	import org.apache.sysds.test.TestUtils;
	import org.apache.sysds.utils.Statistics;

	/**
	*
	*
	*/
	public class FullAggregateTest extends AutomatedTestBase
	{
	private final static String TEST_NAME1 = "AllSum";
	private final static String TEST_NAME2 = "AllMean";
	private final static String TEST_NAME3 = "AllMax";
	private final static String TEST_NAME4 = "AllMin";
	private final static String TEST_NAME5 = "AllProd";
	private final static String TEST_NAME6 = "DiagSum"; //trace

	private final static String TEST_DIR = "functions/aggregate/";
	private static final String TEST_CLASS_DIR = TEST_DIR + FullAggregateTest.class.getSimpleName() + "/";
	private final static double eps = 1e-10;

	private final static int rows1 = 1005;
	private final static int cols1 = 1;
	private final static int cols2 = 1079;
	private final static double sparsity1 = 0.1;
	private final static double sparsity2 = 0.7;

	private enum OpType{
	SUM,
	MEAN,
	MAX,
	MIN,
	PROD,
	TRACE
	}

	@Override
	public void setUp()
	{
	addTestConfiguration(TEST_NAME1, new TestConfiguration(TEST_CLASS_DIR, TEST_NAME1, new String[]{"B"}));
	addTestConfiguration(TEST_NAME2, new TestConfiguration(TEST_CLASS_DIR, TEST_NAME2, new String[]{"B"}));
	addTestConfiguration(TEST_NAME3, new TestConfiguration(TEST_CLASS_DIR, TEST_NAME3, new String[]{"B"}));
	addTestConfiguration(TEST_NAME4, new TestConfiguration(TEST_CLASS_DIR, TEST_NAME4, new String[]{"B"}));
	addTestConfiguration(TEST_NAME5, new TestConfiguration(TEST_CLASS_DIR, TEST_NAME5, new String[]{"B"}));
	addTestConfiguration(TEST_NAME6, new TestConfiguration(TEST_CLASS_DIR, TEST_NAME6, new String[]{"B"}));

	if (TEST_CACHE_ENABLED) {
	setOutAndExpectedDeletionDisabled(true);
	}
	}

	@BeforeClass
	public static void init()
	{
	TestUtils.clearDirectory(TEST_DATA_DIR + TEST_CLASS_DIR);
	}

	@AfterClass
	public static void cleanUp()
	{
	if (TEST_CACHE_ENABLED) {
	TestUtils.clearDirectory(TEST_DATA_DIR + TEST_CLASS_DIR);
	}
	}

	@Test
	public void testSumDenseMatrixCP()
	{
	runColAggregateOperationTest(OpType.SUM, false, false, ExecType.CP);
	}

	@Test
	public void testMeanDenseMatrixCP()
	{
	runColAggregateOperationTest(OpType.MEAN, false, false, ExecType.CP);
	}

	@Test
	public void testMaxDenseMatrixCP()
	{
	runColAggregateOperationTest(OpType.MAX, false, false, ExecType.CP);
	}

	@Test
	public void testMinDenseMatrixCP()
	{
	runColAggregateOperationTest(OpType.MIN, false, false, ExecType.CP);
	}

	@Test
	public void testProdDenseMatrixCP()
	{
	runColAggregateOperationTest(OpType.PROD, false, false, ExecType.CP);
	}

	@Test
	public void testTraceDenseMatrixCP()
	{
	runColAggregateOperationTest(OpType.TRACE, false, false, ExecType.CP);
	}

	@Test
	public void testSumDenseVectorCP()
	{
	runColAggregateOperationTest(OpType.SUM, false, true, ExecType.CP);
	}

	@Test
	public void testMeanDenseVectorCP()
	{
	runColAggregateOperationTest(OpType.MEAN, false, true, ExecType.CP);
	}

	@Test
	public void testMaxDenseVectorCP()
	{
	runColAggregateOperationTest(OpType.MAX, false, true, ExecType.CP);
	}

	@Test
	public void testMinDenseVectorCP()
	{
	runColAggregateOperationTest(OpType.MIN, false, true, ExecType.CP);
	}

	@Test
	public void testProdDenseVectorCP()
	{
	runColAggregateOperationTest(OpType.PROD, false, true, ExecType.CP);
	}

	@Test
	public void testTraceDenseVectorCP()
	{
	runColAggregateOperationTest(OpType.TRACE, false, true, ExecType.CP);
	}

	@Test
	public void testSumSparseMatrixCP()
	{
	runColAggregateOperationTest(OpType.SUM, true, false, ExecType.CP);
	}

	@Test
	public void testMeanSparseMatrixCP()
	{
	runColAggregateOperationTest(OpType.MEAN, true, false, ExecType.CP);
	}

	@Test
	public void testMaxSparseMatrixCP()
	{
	runColAggregateOperationTest(OpType.MAX, true, false, ExecType.CP);
	}

	@Test
	public void testMinSparseMatrixCP()
	{
	runColAggregateOperationTest(OpType.MIN, true, false, ExecType.CP);
	}

	@Test
	public void testProdSparseMatrixCP()
	{
	runColAggregateOperationTest(OpType.PROD, true, false, ExecType.CP);
	}

	@Test
	public void testTraceSparseMatrixCP()
	{
	runColAggregateOperationTest(OpType.TRACE, true, false, ExecType.CP);
	}

	@Test
	public void testSumSparseVectorCP()
	{
	runColAggregateOperationTest(OpType.SUM, true, true, ExecType.CP);
	}

	@Test
	public void testMeanSparseVectorCP()
	{
	runColAggregateOperationTest(OpType.MEAN, true, true, ExecType.CP);
	}

	@Test
	public void testMaxSparseVectorCP()
	{
	runColAggregateOperationTest(OpType.MAX, true, true, ExecType.CP);
	}

	@Test
	public void testMinSparseVectorCP()
	{
	runColAggregateOperationTest(OpType.MIN, true, true, ExecType.CP);
	}

	@Test
	public void testProdSparseVectorCP()
	{
	runColAggregateOperationTest(OpType.PROD, true, true, ExecType.CP);
	}

	@Test
	public void testTraceSparseVectorCP()
	{
	runColAggregateOperationTest(OpType.TRACE, true, true, ExecType.CP);
	}

	@Test
	public void testSumDenseMatrixSP()
	{
	runColAggregateOperationTest(OpType.SUM, false, false, ExecType.SPARK);
	}

	@Test
	public void testMeanDenseMatrixSP()
	{
	runColAggregateOperationTest(OpType.MEAN, false, false, ExecType.SPARK);
	}

	@Test
	public void testMaxDenseMatrixSP()
	{
	runColAggregateOperationTest(OpType.MAX, false, false, ExecType.SPARK);
	}

	@Test
	public void testMinDenseMatrixSP()
	{
	runColAggregateOperationTest(OpType.MIN, false, false, ExecType.SPARK);
	}

	@Test
	public void testProdDenseMatrixSP()
	{
	runColAggregateOperationTest(OpType.PROD, false, false, ExecType.SPARK);
	}

	@Test
	public void testTraceDenseMatrixSP()
	{
	runColAggregateOperationTest(OpType.TRACE, false, false, ExecType.SPARK);
	}

	@Test
	public void testSumDenseVectorSP()
	{
	runColAggregateOperationTest(OpType.SUM, false, true, ExecType.SPARK);
	}

	@Test
	public void testMeanDenseVectorSP()
	{
	runColAggregateOperationTest(OpType.MEAN, false, true, ExecType.SPARK);
	}

	@Test
	public void testMaxDenseVectorSP()
	{
	runColAggregateOperationTest(OpType.MAX, false, true, ExecType.SPARK);
	}

	@Test
	public void testMinDenseVectorSP()
	{
	runColAggregateOperationTest(OpType.MIN, false, true, ExecType.SPARK);
	}

	@Test
	public void testProdDenseVectorSP()
	{
	runColAggregateOperationTest(OpType.PROD, false, true, ExecType.SPARK);
	}

	@Test
	public void testTraceDenseVectorSP()
	{
	runColAggregateOperationTest(OpType.TRACE, false, true, ExecType.SPARK);
	}

	@Test
	public void testSumSparseMatrixSP()
	{
	runColAggregateOperationTest(OpType.SUM, true, false, ExecType.SPARK);
	}

	@Test
	public void testMeanSparseMatrixSP()
	{
	runColAggregateOperationTest(OpType.MEAN, true, false, ExecType.SPARK);
	}

	@Test
	public void testMaxSparseMatrixSP()
	{
	runColAggregateOperationTest(OpType.MAX, true, false, ExecType.SPARK);
	}

	@Test
	public void testMinSparseMatrixSP()
	{
	runColAggregateOperationTest(OpType.MIN, true, false, ExecType.SPARK);
	}

	@Test
	public void testProdSparseMatrixSP()
	{
	runColAggregateOperationTest(OpType.PROD, true, false, ExecType.SPARK);
	}

	@Test
	public void testTraceSparseMatrixSP()
	{
	runColAggregateOperationTest(OpType.TRACE, true, false, ExecType.SPARK);
	}

	@Test
	public void testSumSparseVectorSP()
	{
	runColAggregateOperationTest(OpType.SUM, true, true, ExecType.SPARK);
	}

	@Test
	public void testMeanSparseVectorSP()
	{
	runColAggregateOperationTest(OpType.MEAN, true, true, ExecType.SPARK);
	}

	@Test
	public void testMaxSparseVectorSP()
	{
	runColAggregateOperationTest(OpType.MAX, true, true, ExecType.SPARK);
	}

	@Test
	public void testMinSparseVectorSP()
	{
	runColAggregateOperationTest(OpType.MIN, true, true, ExecType.SPARK);
	}

	@Test
	public void testProdSparseVectorSP()
	{
	runColAggregateOperationTest(OpType.PROD, true, true, ExecType.SPARK);
	}

	@Test
	public void testTraceSparseVectorSP()
	{
	runColAggregateOperationTest(OpType.TRACE, true, true, ExecType.SPARK);
	}

	private void runColAggregateOperationTest( OpType type, boolean sparse, boolean vector, ExecType instType)
	{
	ExecMode platformOld = rtplatform;
	switch( instType ){
	case SPARK: rtplatform = ExecMode.SPARK; break;
	default: rtplatform = ExecMode.HYBRID; break;
	}

	boolean sparkConfigOld = DMLScript.USE_LOCAL_SPARK_CONFIG;
	if( rtplatform == ExecMode.SPARK )
	DMLScript.USE_LOCAL_SPARK_CONFIG = true;

	try
	{
	String TEST_NAME = null;
	switch( type )
	{
	case SUM: TEST_NAME = TEST_NAME1; break;
	case MEAN: TEST_NAME = TEST_NAME2; break;
	case MAX: TEST_NAME = TEST_NAME3; break;
	case MIN: TEST_NAME = TEST_NAME4; break;
	case PROD: TEST_NAME = TEST_NAME5; break;
	case TRACE: TEST_NAME = TEST_NAME6; break;
	}

	int cols = (vector) ? cols1 : cols2;
	int rows = (type==OpType.TRACE) ? cols : rows1;
	double sparsity = (sparse) ? sparsity1 : sparsity2;

	String TEST_CACHE_DIR = "";
	if (TEST_CACHE_ENABLED)
	{
	TEST_CACHE_DIR = type.ordinal() + "_" + rows + "_" + cols + "_" + sparsity + "/";
	}

	TestConfiguration config = getTestConfiguration(TEST_NAME);
	loadTestConfiguration(config, TEST_CACHE_DIR);

	/* This is for running the junit test the new way, i.e., construct the arguments directly */
	String HOME = SCRIPT_DIR + TEST_DIR;
	fullDMLScriptName = HOME + TEST_NAME + ".dml";
	programArgs = new String[]{"-args", input("A"),
	Integer.toString(rows), Integer.toString(cols), output("B") };

	fullRScriptName = HOME + TEST_NAME + ".R";
	rCmd = "Rscript" + " " + fullRScriptName + " " + inputDir() + " " + expectedDir();

	//generate actual dataset
	double[][] A = getRandomMatrix(rows, cols, -0.05, 1, sparsity, 7);
	writeInputMatrix("A", A, true);

	runTest(true, false, null, -1);
	if( instType==ExecType.CP ) //in CP no MR jobs should be executed
	Assert.assertEquals("Unexpected number of executed MR jobs.", 0, Statistics.getNoOfExecutedSPInst());

	runRScript(true);

	//compare matrices
	HashMap<CellIndex, Double> dmlfile = readDMLMatrixFromOutputDir("B");
	HashMap<CellIndex, Double> rfile = readRMatrixFromExpectedDir("B");
	TestUtils.compareMatrices(dmlfile, rfile, eps, "Stat-DML", "Stat-R");
	}
	finally
	{
	rtplatform = platformOld;
	DMLScript.USE_LOCAL_SPARK_CONFIG = sparkConfigOld;
	}
	}
	}