src/test/java/org/apache/sysds/test/functions/aggregate/FullColAggregateTest.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.BeforeClass;
 import org.junit.Test;
 import org.apache.sysds.api.DMLScript;
 import org.apache.sysds.common.Types.ExecMode;
 import org.apache.sysds.hops.OptimizerUtils;
 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;

 /**
  * NOTES:
  *  * the output definition of DML and R differs for col*; R always returns a column vector
  *    while DML returns a row vector.
  *  * the R package Matrix does not support colMins and colMaxs; hence, we use the matrixStats package
  *
  */
 public class FullColAggregateTest extends AutomatedTestBase
 {
 	private final static String TEST_NAME1 = "ColSums";
 	private final static String TEST_NAME2 = "ColMeans";
 	private final static String TEST_NAME3 = "ColMaxs";
 	private final static String TEST_NAME4 = "ColMins";

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

 	private final static int rows = 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{
 		COL_SUMS,
 		COL_MEANS,
 		COL_MAX,
 		COL_MIN
 	}


 	@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"}));

 		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 testColSumsDenseMatrixCP()
 	{
 		runColAggregateOperationTest(OpType.COL_SUMS, false, false, ExecType.CP);
 	}

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

 	private void runColAggregateOperationTest( OpType type, boolean sparse, boolean vector, ExecType instType)
 	{
 		runColAggregateOperationTest(type, sparse, vector, instType, true); //by default apply algebraic simplification
 	}

 	private void runColAggregateOperationTest( OpType type, boolean sparse, boolean vector, ExecType instType, boolean rewrites)
 	{
 		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;

 		boolean oldRewritesFlag = OptimizerUtils.ALLOW_ALGEBRAIC_SIMPLIFICATION;
 		OptimizerUtils.ALLOW_ALGEBRAIC_SIMPLIFICATION = rewrites;

 		try
 		{
 			String TEST_NAME = null;
 			switch( type )
 			{
 				case COL_SUMS: TEST_NAME = TEST_NAME1; break;
 				case COL_MEANS: TEST_NAME = TEST_NAME2; break;
 				case COL_MAX: TEST_NAME = TEST_NAME3; break;
 				case COL_MIN: TEST_NAME = TEST_NAME4; break;
 			}

 			int cols = (vector) ? cols1 : cols2;
 			double sparsity = (sparse) ? sparsity1 : sparsity2;

 			String TEST_CACHE_DIR = "";
 			if (TEST_CACHE_ENABLED)
 			{
 				TEST_CACHE_DIR = type.ordinal() + "_" + 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);

 			boolean exceptionExpected = false;
 			runTest(true, exceptionExpected, null, -1);

 			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;
 			OptimizerUtils.ALLOW_ALGEBRAIC_SIMPLIFICATION = oldRewritesFlag;
 		}
 	}
 }
	/*
	* 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.BeforeClass;
	import org.junit.Test;
	import org.apache.sysds.api.DMLScript;
	import org.apache.sysds.common.Types.ExecMode;
	import org.apache.sysds.hops.OptimizerUtils;
	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;

	/**
	* NOTES:
	* * the output definition of DML and R differs for col*; R always returns a column vector
	* while DML returns a row vector.
	* * the R package Matrix does not support colMins and colMaxs; hence, we use the matrixStats package
	*
	*/
	public class FullColAggregateTest extends AutomatedTestBase
	{
	private final static String TEST_NAME1 = "ColSums";
	private final static String TEST_NAME2 = "ColMeans";
	private final static String TEST_NAME3 = "ColMaxs";
	private final static String TEST_NAME4 = "ColMins";

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

	private final static int rows = 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{
	COL_SUMS,
	COL_MEANS,
	COL_MAX,
	COL_MIN
	}


	@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"}));

	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 testColSumsDenseMatrixCP()
	{
	runColAggregateOperationTest(OpType.COL_SUMS, false, false, ExecType.CP);
	}

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

	private void runColAggregateOperationTest( OpType type, boolean sparse, boolean vector, ExecType instType)
	{
	runColAggregateOperationTest(type, sparse, vector, instType, true); //by default apply algebraic simplification
	}

	private void runColAggregateOperationTest( OpType type, boolean sparse, boolean vector, ExecType instType, boolean rewrites)
	{
	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;

	boolean oldRewritesFlag = OptimizerUtils.ALLOW_ALGEBRAIC_SIMPLIFICATION;
	OptimizerUtils.ALLOW_ALGEBRAIC_SIMPLIFICATION = rewrites;

	try
	{
	String TEST_NAME = null;
	switch( type )
	{
	case COL_SUMS: TEST_NAME = TEST_NAME1; break;
	case COL_MEANS: TEST_NAME = TEST_NAME2; break;
	case COL_MAX: TEST_NAME = TEST_NAME3; break;
	case COL_MIN: TEST_NAME = TEST_NAME4; break;
	}

	int cols = (vector) ? cols1 : cols2;
	double sparsity = (sparse) ? sparsity1 : sparsity2;

	String TEST_CACHE_DIR = "";
	if (TEST_CACHE_ENABLED)
	{
	TEST_CACHE_DIR = type.ordinal() + "_" + 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);

	boolean exceptionExpected = false;
	runTest(true, exceptionExpected, null, -1);

	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;
	OptimizerUtils.ALLOW_ALGEBRAIC_SIMPLIFICATION = oldRewritesFlag;
	}
	}
	}