src/test/java/org/apache/sysds/test/functions/parfor/misc/ParForRulebasedOptimizerTest.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.parfor.misc;

 import java.util.HashMap;

 import org.junit.Test;
 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;

 public class ParForRulebasedOptimizerTest extends AutomatedTestBase
 {
 	private final static String TEST_NAME1 = "parfor_optimizer1"; //+b for dml
 	private final static String TEST_NAME2 = "parfor_optimizer2"; //+b for dml
 	private final static String TEST_NAME3 = "parfor_optimizer3"; //+b for dml
 	private final static String TEST_DIR = "functions/parfor/";
 	private final static String TEST_CLASS_DIR = TEST_DIR + ParForRulebasedOptimizerTest.class.getSimpleName() + "/";
 	private final static double eps = 1e-10;

 	private final static int rows1 = 1000; //small CP
 	private final static int rows2 = 10000; //large MR

 	private final static int cols11 = 50;  //small single parfor
 	private final static int cols12 = 500; //large single parfor

 	private final static int cols21 = 8;  //small nested parfor
 	private final static int cols22 = 50; //large nested parfor
 	private final static int cols31 = 2;  //small nested parfor
 	private final static int cols32 = 8; //large nested parfor
 	private final static double sparsity = 0.7;

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

 	@Test
 	public void testParForRulebasedOptimizerCorrelationSmallSmall() {
 		runParForOptimizerTest(1, false, false, false);
 	}

 	@Test
 	public void testParForRulebasedOptimizerCorrelationSmallLarge() {
 		runParForOptimizerTest(1, false, true, false);
 	}

 	@Test
 	public void testParForRulebasedOptimizerCorrelationLargeSmall() {
 		runParForOptimizerTest(1, true, false, false);
 	}

 	@Test
 	public void testParForRulebasedOptimizerCorrelationLargeLarge() {
 		runParForOptimizerTest(1, true, true, false);
 	}

 	@Test
 	public void testParForRulebasedOptimizerBivariateStatsSmallSmall() {
 		runParForOptimizerTest(2, false, false, false);
 	}

 	@Test
 	public void testParForRulebasedOptimizerBivariateStatsSmallLarge() {
 		runParForOptimizerTest(2, false, true, false);
 	}

 	@Test
 	public void testParForRulebasedOptimizerBivariateStatsLargeSmall() {
 		runParForOptimizerTest(2, true, false, false);
 	}

 	@Test
 	public void testParForRulebasedOptimizerBivariateStatsLargeLarge() {
 		runParForOptimizerTest(2, true, true, false);
 	}

 	@Test
 	public void testParForRulebasedOptimizerFunctionInvocationSmallSmall() {
 		runParForOptimizerTest(3, false, false, false);
 	}

 	@Test
 	public void testParForRulebasedOptimizerFunctionInvocationSmallLarge() {
 		runParForOptimizerTest(3, false, true, false);
 	}

 	@Test
 	public void testParForRulebasedOptimizerFunctionInvocationLargeSmall() {
 		runParForOptimizerTest(3, true, false, false);
 	}

 	@Test
 	public void testParForRulebasedOptimizerFunctionInvocationLargeLarge() {
 		runParForOptimizerTest(3, true, true, false);
 	}

 	@Test
 	public void testParForHeuristicOptimizerCorrelationSmallSmall() {
 		runParForOptimizerTest(1, false, false, true);
 	}

 	@Test
 	public void testParForHeuristicOptimizerCorrelationSmallLarge() {
 		runParForOptimizerTest(1, false, true, true);
 	}

 	@Test
 	public void testParForHeuristicOptimizerCorrelationLargeSmall() {
 		runParForOptimizerTest(1, true, false, true);
 	}

 	@Test
 	public void testParForHeuristicOptimizerCorrelationLargeLarge() {
 		runParForOptimizerTest(1, true, true, true);
 	}

 	@Test
 	public void testParForHeuristicOptimizerBivariateStatsSmallSmall() {
 		runParForOptimizerTest(2, false, false, true);
 	}

 	@Test
 	public void testParForHeuristicOptimizerBivariateStatsSmallLarge() {
 		runParForOptimizerTest(2, false, true, true);
 	}

 	@Test
 	public void testParForHeuristicOptimizerBivariateStatsLargeSmall() {
 		runParForOptimizerTest(2, true, false, true);
 	}

 	@Test
 	public void testParForHeuristicOptimizerBivariateStatsLargeLarge() {
 		runParForOptimizerTest(2, true, true, true);
 	}

 	@Test
 	public void testParForHeuristicOptimizerFunctionInvocationSmallSmall() {
 		runParForOptimizerTest(3, false, false, true);
 	}

 	@Test
 	public void testParForHeuristicOptimizerFunctionInvocationSmallLarge() {
 		runParForOptimizerTest(3, false, true, true);
 	}

 	@Test
 	public void testParForHeuristicOptimizerFunctionInvocationLargeSmall() {
 		runParForOptimizerTest(3, true, false, true);
 	}

 	@Test
 	public void testParForHeuristicOptimizerFunctionInvocationLargeLarge() {
 		runParForOptimizerTest(3, true, true, true);
 	}


 	private void runParForOptimizerTest( int scriptNum, boolean largeRows, boolean largeCols, boolean timebasedOpt )
 	{
 		//find right rows and cols configuration
 		int rows=-1, cols=-1;
 		if( largeRows )
 			rows = rows2;
 		else
 			rows = rows1;
 		if( largeCols ){
 			switch(scriptNum) {
 				case 1: cols=cols22; break;
 				case 2: cols=cols32; break;
 				case 3: cols=cols12; break;
 			}
 		}
 		else{
 			switch(scriptNum) {
 				case 1: cols=cols21; break;
 				case 2: cols=cols31; break;
 				case 3: cols=cols11; break;
 			}
 		}

 		//run actual test
 		switch( scriptNum ) {
 			case 1:
 				runUnaryTest(scriptNum, timebasedOpt, rows, cols);
 				break;
 			case 2:
 				runNaryTest(scriptNum, timebasedOpt, rows, cols);
 				break;
 			case 3:
 				runUnaryTest(scriptNum, timebasedOpt, rows, cols);
 				break;
 		}
 	}

 	private void runUnaryTest(int scriptNum, boolean timebasedOpt, int rows, int cols )
 	{
 		TestConfiguration config = null;
 		String HOME = SCRIPT_DIR + TEST_DIR;
 		if( scriptNum==1 ) {
 			config=getTestConfiguration(TEST_NAME1);
 			String testname = TEST_NAME1 + (timebasedOpt ? "b" : "");
 			fullDMLScriptName = HOME + testname + ".dml";
 		}
 		else if( scriptNum==3 ) {
 			config=getTestConfiguration(TEST_NAME3);
 			String testname = TEST_NAME3 + (timebasedOpt ? "b" : "");
 			fullDMLScriptName = HOME + testname + ".dml";
 		}

 		config.addVariable("rows", rows);
 		config.addVariable("cols", cols);
 		loadTestConfiguration(config);

 		if( scriptNum==1 ) {
 			programArgs = new String[]{ "-args", input("V"),
 				Integer.toString(rows), Integer.toString(cols),
 				output("R") };
 			rCmd = "Rscript" + " " + HOME + TEST_NAME1 + ".R" + " " +
 				inputDir() + " " + expectedDir();
 		}
 		else if( scriptNum==3 ) {
 			programArgs = new String[]{ "-args", input("V"),
 				Integer.toString(rows), Integer.toString(cols),
 				Integer.toString(cols/2),
 				output("R") };
 			rCmd = "Rscript" + " " + HOME + TEST_NAME3 + ".R" + " " +
 				inputDir() + " " + expectedDir();
 		}

 		long seed = System.nanoTime();
 		double[][] V = getRandomMatrix(rows, cols, 0, 1, sparsity, seed);
 		writeInputMatrix("V", V, true);

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

 		runRScript(true);

 		//compare matrices
 		HashMap<CellIndex, Double> dmlfile = readDMLMatrixFromHDFS("R");
 		HashMap<CellIndex, Double> rfile  = readRMatrixFromFS("Rout");
 		TestUtils.compareMatrices(dmlfile, rfile, eps, "DML", "R");
 	}

 	private void runNaryTest(int scriptNum, boolean timebasedOpt, int rows, int cols)
 	{
 		TestConfiguration config = getTestConfiguration(TEST_NAME2);
 		config.addVariable("rows", rows);
 		config.addVariable("cols", cols);
 		loadTestConfiguration(config);

 		/* This is for running the junit test the new way, i.e., construct the arguments directly */
 		String HOME = SCRIPT_DIR + TEST_DIR;
 		String testname = TEST_NAME2 + (timebasedOpt ? "b" : "");
 		fullDMLScriptName = HOME + testname + ".dml";
 		programArgs = new String[]{"-explain", "-args",
 			input("D"),
 			input("S1"), input("S2"),
 			input("K1"), input("K2"),
 			output("bivarstats"),
 			Integer.toString(rows),
 			Integer.toString(cols),
 			Integer.toString(cols),
 			Integer.toString(cols*cols),
 			Integer.toString(7) };

 		rCmd = "Rscript" + " " + HOME + TEST_NAME2 + ".R" + " " +
 			inputDir() + " " + Integer.toString(7) + " " + expectedDir();

 		//generate actual dataset
 		double[][] D = getRandomMatrix(rows, cols, 1, 7, 1.0, 7777);
 		double[] Dkind = new double[cols];
 		for( int i=0; i<cols; i++ )
 		{
 			Dkind[i]=(i%3)+1;//kind 1,2,3
 			if( Dkind[i]!=1 )
 				TestUtils.floor(D,i); //for ordinal and categorical vars
 		}
 		writeInputMatrix("D", D, true);

 		//generate attribute sets
 		double[][] S1 = getRandomMatrix(1, cols, 1, cols+1-eps, 1, 1112);
 		double[][] S2 = getRandomMatrix(1, cols, 1, cols+1-eps, 1, 1113);
 		TestUtils.floor(S1);
 		TestUtils.floor(S2);
 		writeInputMatrix("S1", S1, true);
 		writeInputMatrix("S2", S2, true);

 		//generate kind for attributes (1,2,3)
 		double[][] K1 = new double[1][cols];
 		double[][] K2 = new double[1][cols];
 		for( int i=0; i<cols; i++ ) {
 			K1[0][i] = Dkind[(int)S1[0][i]-1];
 			K2[0][i] = Dkind[(int)S2[0][i]-1];
 		}
 		writeInputMatrix("K1", K1, true);
 		writeInputMatrix("K2", K2, true);

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

 		runRScript(true);

 		//compare matrices
 		for( String out : new String[]{"bivar.stats", "category.counts", "category.means",  "category.variances" } ) {
 			HashMap<CellIndex, Double> dmlfile = readDMLMatrixFromHDFS("bivarstats/"+out);
 			HashMap<CellIndex, Double> rfile  = readRMatrixFromFS(out);
 			TestUtils.compareMatrices(dmlfile, rfile, eps, "Stat-DML", "Stat-R");
 		}
 	}
 }
	/*
	* 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.parfor.misc;

	import java.util.HashMap;

	import org.junit.Test;
	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;

	public class ParForRulebasedOptimizerTest extends AutomatedTestBase
	{
	private final static String TEST_NAME1 = "parfor_optimizer1"; //+b for dml
	private final static String TEST_NAME2 = "parfor_optimizer2"; //+b for dml
	private final static String TEST_NAME3 = "parfor_optimizer3"; //+b for dml
	private final static String TEST_DIR = "functions/parfor/";
	private final static String TEST_CLASS_DIR = TEST_DIR + ParForRulebasedOptimizerTest.class.getSimpleName() + "/";
	private final static double eps = 1e-10;

	private final static int rows1 = 1000; //small CP
	private final static int rows2 = 10000; //large MR

	private final static int cols11 = 50; //small single parfor
	private final static int cols12 = 500; //large single parfor

	private final static int cols21 = 8; //small nested parfor
	private final static int cols22 = 50; //large nested parfor
	private final static int cols31 = 2; //small nested parfor
	private final static int cols32 = 8; //large nested parfor
	private final static double sparsity = 0.7;

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

	@Test
	public void testParForRulebasedOptimizerCorrelationSmallSmall() {
	runParForOptimizerTest(1, false, false, false);
	}

	@Test
	public void testParForRulebasedOptimizerCorrelationSmallLarge() {
	runParForOptimizerTest(1, false, true, false);
	}

	@Test
	public void testParForRulebasedOptimizerCorrelationLargeSmall() {
	runParForOptimizerTest(1, true, false, false);
	}

	@Test
	public void testParForRulebasedOptimizerCorrelationLargeLarge() {
	runParForOptimizerTest(1, true, true, false);
	}

	@Test
	public void testParForRulebasedOptimizerBivariateStatsSmallSmall() {
	runParForOptimizerTest(2, false, false, false);
	}

	@Test
	public void testParForRulebasedOptimizerBivariateStatsSmallLarge() {
	runParForOptimizerTest(2, false, true, false);
	}

	@Test
	public void testParForRulebasedOptimizerBivariateStatsLargeSmall() {
	runParForOptimizerTest(2, true, false, false);
	}

	@Test
	public void testParForRulebasedOptimizerBivariateStatsLargeLarge() {
	runParForOptimizerTest(2, true, true, false);
	}

	@Test
	public void testParForRulebasedOptimizerFunctionInvocationSmallSmall() {
	runParForOptimizerTest(3, false, false, false);
	}

	@Test
	public void testParForRulebasedOptimizerFunctionInvocationSmallLarge() {
	runParForOptimizerTest(3, false, true, false);
	}

	@Test
	public void testParForRulebasedOptimizerFunctionInvocationLargeSmall() {
	runParForOptimizerTest(3, true, false, false);
	}

	@Test
	public void testParForRulebasedOptimizerFunctionInvocationLargeLarge() {
	runParForOptimizerTest(3, true, true, false);
	}

	@Test
	public void testParForHeuristicOptimizerCorrelationSmallSmall() {
	runParForOptimizerTest(1, false, false, true);
	}

	@Test
	public void testParForHeuristicOptimizerCorrelationSmallLarge() {
	runParForOptimizerTest(1, false, true, true);
	}

	@Test
	public void testParForHeuristicOptimizerCorrelationLargeSmall() {
	runParForOptimizerTest(1, true, false, true);
	}

	@Test
	public void testParForHeuristicOptimizerCorrelationLargeLarge() {
	runParForOptimizerTest(1, true, true, true);
	}

	@Test
	public void testParForHeuristicOptimizerBivariateStatsSmallSmall() {
	runParForOptimizerTest(2, false, false, true);
	}

	@Test
	public void testParForHeuristicOptimizerBivariateStatsSmallLarge() {
	runParForOptimizerTest(2, false, true, true);
	}

	@Test
	public void testParForHeuristicOptimizerBivariateStatsLargeSmall() {
	runParForOptimizerTest(2, true, false, true);
	}

	@Test
	public void testParForHeuristicOptimizerBivariateStatsLargeLarge() {
	runParForOptimizerTest(2, true, true, true);
	}

	@Test
	public void testParForHeuristicOptimizerFunctionInvocationSmallSmall() {
	runParForOptimizerTest(3, false, false, true);
	}

	@Test
	public void testParForHeuristicOptimizerFunctionInvocationSmallLarge() {
	runParForOptimizerTest(3, false, true, true);
	}

	@Test
	public void testParForHeuristicOptimizerFunctionInvocationLargeSmall() {
	runParForOptimizerTest(3, true, false, true);
	}

	@Test
	public void testParForHeuristicOptimizerFunctionInvocationLargeLarge() {
	runParForOptimizerTest(3, true, true, true);
	}


	private void runParForOptimizerTest( int scriptNum, boolean largeRows, boolean largeCols, boolean timebasedOpt )
	{
	//find right rows and cols configuration
	int rows=-1, cols=-1;
	if( largeRows )
	rows = rows2;
	else
	rows = rows1;
	if( largeCols ){
	switch(scriptNum) {
	case 1: cols=cols22; break;
	case 2: cols=cols32; break;
	case 3: cols=cols12; break;
	}
	}
	else{
	switch(scriptNum) {
	case 1: cols=cols21; break;
	case 2: cols=cols31; break;
	case 3: cols=cols11; break;
	}
	}

	//run actual test
	switch( scriptNum ) {
	case 1:
	runUnaryTest(scriptNum, timebasedOpt, rows, cols);
	break;
	case 2:
	runNaryTest(scriptNum, timebasedOpt, rows, cols);
	break;
	case 3:
	runUnaryTest(scriptNum, timebasedOpt, rows, cols);
	break;
	}
	}

	private void runUnaryTest(int scriptNum, boolean timebasedOpt, int rows, int cols )
	{
	TestConfiguration config = null;
	String HOME = SCRIPT_DIR + TEST_DIR;
	if( scriptNum==1 ) {
	config=getTestConfiguration(TEST_NAME1);
	String testname = TEST_NAME1 + (timebasedOpt ? "b" : "");
	fullDMLScriptName = HOME + testname + ".dml";
	}
	else if( scriptNum==3 ) {
	config=getTestConfiguration(TEST_NAME3);
	String testname = TEST_NAME3 + (timebasedOpt ? "b" : "");
	fullDMLScriptName = HOME + testname + ".dml";
	}

	config.addVariable("rows", rows);
	config.addVariable("cols", cols);
	loadTestConfiguration(config);

	if( scriptNum==1 ) {
	programArgs = new String[]{ "-args", input("V"),
	Integer.toString(rows), Integer.toString(cols),
	output("R") };
	rCmd = "Rscript" + " " + HOME + TEST_NAME1 + ".R" + " " +
	inputDir() + " " + expectedDir();
	}
	else if( scriptNum==3 ) {
	programArgs = new String[]{ "-args", input("V"),
	Integer.toString(rows), Integer.toString(cols),
	Integer.toString(cols/2),
	output("R") };
	rCmd = "Rscript" + " " + HOME + TEST_NAME3 + ".R" + " " +
	inputDir() + " " + expectedDir();
	}

	long seed = System.nanoTime();
	double[][] V = getRandomMatrix(rows, cols, 0, 1, sparsity, seed);
	writeInputMatrix("V", V, true);

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

	runRScript(true);

	//compare matrices
	HashMap<CellIndex, Double> dmlfile = readDMLMatrixFromHDFS("R");
	HashMap<CellIndex, Double> rfile = readRMatrixFromFS("Rout");
	TestUtils.compareMatrices(dmlfile, rfile, eps, "DML", "R");
	}

	private void runNaryTest(int scriptNum, boolean timebasedOpt, int rows, int cols)
	{
	TestConfiguration config = getTestConfiguration(TEST_NAME2);
	config.addVariable("rows", rows);
	config.addVariable("cols", cols);
	loadTestConfiguration(config);

	/* This is for running the junit test the new way, i.e., construct the arguments directly */
	String HOME = SCRIPT_DIR + TEST_DIR;
	String testname = TEST_NAME2 + (timebasedOpt ? "b" : "");
	fullDMLScriptName = HOME + testname + ".dml";
	programArgs = new String[]{"-explain", "-args",
	input("D"),
	input("S1"), input("S2"),
	input("K1"), input("K2"),
	output("bivarstats"),
	Integer.toString(rows),
	Integer.toString(cols),
	Integer.toString(cols),
	Integer.toString(cols*cols),
	Integer.toString(7) };

	rCmd = "Rscript" + " " + HOME + TEST_NAME2 + ".R" + " " +
	inputDir() + " " + Integer.toString(7) + " " + expectedDir();

	//generate actual dataset
	double[][] D = getRandomMatrix(rows, cols, 1, 7, 1.0, 7777);
	double[] Dkind = new double[cols];
	for( int i=0; i<cols; i++ )
	{
	Dkind[i]=(i%3)+1;//kind 1,2,3
	if( Dkind[i]!=1 )
	TestUtils.floor(D,i); //for ordinal and categorical vars
	}
	writeInputMatrix("D", D, true);

	//generate attribute sets
	double[][] S1 = getRandomMatrix(1, cols, 1, cols+1-eps, 1, 1112);
	double[][] S2 = getRandomMatrix(1, cols, 1, cols+1-eps, 1, 1113);
	TestUtils.floor(S1);
	TestUtils.floor(S2);
	writeInputMatrix("S1", S1, true);
	writeInputMatrix("S2", S2, true);

	//generate kind for attributes (1,2,3)
	double[][] K1 = new double[1][cols];
	double[][] K2 = new double[1][cols];
	for( int i=0; i<cols; i++ ) {
	K1[0][i] = Dkind[(int)S1[0][i]-1];
	K2[0][i] = Dkind[(int)S2[0][i]-1];
	}
	writeInputMatrix("K1", K1, true);
	writeInputMatrix("K2", K2, true);

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

	runRScript(true);

	//compare matrices
	for( String out : new String[]{"bivar.stats", "category.counts", "category.means", "category.variances" } ) {
	HashMap<CellIndex, Double> dmlfile = readDMLMatrixFromHDFS("bivarstats/"+out);
	HashMap<CellIndex, Double> rfile = readRMatrixFromFS(out);
	TestUtils.compareMatrices(dmlfile, rfile, eps, "Stat-DML", "Stat-R");
	}
	}
	}