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/*
* Licensed to the Apache Software Foundation (ASF) under one
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* 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
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* KIND, either express or implied. See the License for the
* specific language governing permissions and limitations
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package org.apache.sysds.test.functions.parfor.partition;
import java.util.HashMap;
import org.junit.Test;
import org.apache.sysds.api.DMLScript;
import org.apache.sysds.common.Types.ExecMode;
import org.apache.sysds.hops.Hop;
import org.apache.sysds.runtime.controlprogram.ParForProgramBlock.PDataPartitioner;
import org.apache.sysds.runtime.controlprogram.ParForProgramBlock.PExecMode;
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 ParForRowwiseDataPartitioningTest extends AutomatedTestBase
{
private final static String TEST_NAME = "parfor_rdatapartitioning";
private final static String TEST_DIR = "functions/parfor/";
private final static String TEST_CLASS_DIR = TEST_DIR + ParForRowwiseDataPartitioningTest.class.getSimpleName() + "/";
private final static double eps = 1e-10;
private final static int rows1 = (int)Hop.CPThreshold+1;
private final static int cols1 = 50;
private final static int rows2 = 50;
private final static int cols2 = (int)Hop.CPThreshold+1;
private final static double sparsity1 = 0.7;
private final static double sparsity2 = 0.1d;
@Override
public void setUp() {
addTestConfiguration(TEST_NAME,
new TestConfiguration(TEST_CLASS_DIR, TEST_NAME,
new String[] { "Rout" }) ); //TODO this specification is not intuitive
}
//rowwise
@Test
public void testParForDataPartitioningNoneLocalLargeDense() {
runParForDataPartitioningTest(PDataPartitioner.NONE, null, false, false);
}
@Test
public void testParForDataPartitioningNoneLocalLargeSparse() {
runParForDataPartitioningTest(PDataPartitioner.NONE, PExecMode.LOCAL, false, true);
}
@Test
public void testParForDataPartitioningLocalLocalLargeDense() {
runParForDataPartitioningTest(PDataPartitioner.LOCAL, PExecMode.LOCAL, false, false);
}
@Test
public void testParForDataPartitioningLocalLocalLargeSparse() {
runParForDataPartitioningTest(PDataPartitioner.LOCAL, PExecMode.LOCAL, false, true);
}
@Test
public void testParForDataPartitioningLocalRemoteLargeDense() {
runParForDataPartitioningTest(PDataPartitioner.LOCAL, PExecMode.REMOTE_SPARK, false, false);
}
@Test
public void testParForDataPartitioningLocalRemoteLargeSparse() {
runParForDataPartitioningTest(PDataPartitioner.LOCAL, PExecMode.REMOTE_SPARK, false, true);
}
@Test
public void testParForDataPartitioningRemoteLocalLargeDense()
{
runParForDataPartitioningTest(PDataPartitioner.REMOTE_SPARK, PExecMode.LOCAL, false, false);
}
@Test
public void testParForDataPartitioningRemoteLocalLargeSparse() {
runParForDataPartitioningTest(PDataPartitioner.REMOTE_SPARK, PExecMode.LOCAL, false, true);
}
@Test
public void testParForDataPartitioningRemoteRemoteLargeDense() {
runParForDataPartitioningTest(PDataPartitioner.REMOTE_SPARK, PExecMode.REMOTE_SPARK, false, false);
}
@Test
public void testParForDataPartitioningRemoteRemoteLargeSparse() {
runParForDataPartitioningTest(PDataPartitioner.REMOTE_SPARK, PExecMode.REMOTE_SPARK, false, true);
}
@Test
public void testParForDataPartitioningRemoteSparkLocalLargeDense() {
runParForDataPartitioningTest(PDataPartitioner.REMOTE_SPARK, PExecMode.LOCAL, false, false);
}
@Test
public void testParForDataPartitioningRemoteSparkLocalLargeSparse() {
runParForDataPartitioningTest(PDataPartitioner.REMOTE_SPARK, PExecMode.LOCAL, false, true);
}
@Test
public void testParForDataPartitioningRemoteSparkRemoteLargeDense() {
runParForDataPartitioningTest(PDataPartitioner.REMOTE_SPARK, PExecMode.REMOTE_SPARK, false, false);
}
@Test
public void testParForDataPartitioningRemoteSparkRemoteLargeSparse() {
runParForDataPartitioningTest(PDataPartitioner.REMOTE_SPARK, PExecMode.REMOTE_SPARK, false, true);
}
//rowblockwise
@Test
public void testParForDataPartitioningNoneLocalSmallDense() {
runParForDataPartitioningTest(PDataPartitioner.NONE, null, true, false);
}
@Test
public void testParForDataPartitioningNoneLocalSmallSparse() {
runParForDataPartitioningTest(PDataPartitioner.NONE, PExecMode.LOCAL, true, true);
}
@Test
public void testParForDataPartitioningLocalLocalSmallDense() {
runParForDataPartitioningTest(PDataPartitioner.LOCAL, PExecMode.LOCAL, true, false);
}
@Test
public void testParForDataPartitioningLocalLocalSmallSparse() {
runParForDataPartitioningTest(PDataPartitioner.LOCAL, PExecMode.LOCAL, true, true);
}
@Test
public void testParForDataPartitioningLocalRemoteSmallDense() {
runParForDataPartitioningTest(PDataPartitioner.LOCAL, PExecMode.REMOTE_SPARK, true, false);
}
@Test
public void testParForDataPartitioningLocalRemoteSmallSparse() {
runParForDataPartitioningTest(PDataPartitioner.LOCAL, PExecMode.REMOTE_SPARK, true, true);
}
@Test
public void testParForDataPartitioningRemoteLocalSmallDense() {
runParForDataPartitioningTest(PDataPartitioner.REMOTE_SPARK, PExecMode.LOCAL, true, false);
}
@Test
public void testParForDataPartitioningRemoteLocalSmallSparse() {
runParForDataPartitioningTest(PDataPartitioner.REMOTE_SPARK, PExecMode.LOCAL, true, true);
}
@Test
public void testParForDataPartitioningRemoteRemoteSmallDense() {
runParForDataPartitioningTest(PDataPartitioner.REMOTE_SPARK, PExecMode.REMOTE_SPARK, false, false);
}
@Test
public void testParForDataPartitioningRemoteRemoteSmallSparse() {
runParForDataPartitioningTest(PDataPartitioner.REMOTE_SPARK, PExecMode.REMOTE_SPARK, true, true);
}
@Test
public void testParForDataPartitioningRemoteSparkLocalSmallDense() {
runParForDataPartitioningTest(PDataPartitioner.REMOTE_SPARK, PExecMode.LOCAL, true, false);
}
@Test
public void testParForDataPartitioningRemoteSparkLocalSmallSparse() {
runParForDataPartitioningTest(PDataPartitioner.REMOTE_SPARK, PExecMode.LOCAL, true, true);
}
@Test
public void testParForDataPartitioningRemoteSparkRemoteSmallDense() {
runParForDataPartitioningTest(PDataPartitioner.REMOTE_SPARK, PExecMode.REMOTE_SPARK, false, false);
}
@Test
public void testParForDataPartitioningRemoteSparkRemoteSmallSparse() {
runParForDataPartitioningTest(PDataPartitioner.REMOTE_SPARK, PExecMode.REMOTE_SPARK, true, true);
}
//NOT rowwise
@Test
public void testParForNoDataPartitioningRemoteLocalLargeDense() {
runParForDataPartitioningTest(PDataPartitioner.REMOTE_SPARK, PExecMode.LOCAL, false, false, true);
}
@Test
public void testParForNoDataPartitioningRemoteLocalLargeSparse() {
runParForDataPartitioningTest(PDataPartitioner.REMOTE_SPARK, PExecMode.LOCAL, false, true, true);
}
@Test
public void testParForNoDataPartitioningRemoteSparkLocalLargeDense() {
runParForDataPartitioningTest(PDataPartitioner.REMOTE_SPARK, PExecMode.LOCAL, false, false, true);
}
@Test
public void testParForNoDataPartitioningRemoteSparkLocalLargeSparse() {
runParForDataPartitioningTest(PDataPartitioner.REMOTE_SPARK, PExecMode.LOCAL, false, true, true);
}
private void runParForDataPartitioningTest( PDataPartitioner partitioner, PExecMode mode, boolean small, boolean sparse ) {
runParForDataPartitioningTest(partitioner, mode, small, sparse, false);
}
private void runParForDataPartitioningTest( PDataPartitioner partitioner, PExecMode mode, boolean small, boolean sparse, boolean multiParts )
{
ExecMode oldRT = rtplatform;
boolean oldUseSparkConfig = DMLScript.USE_LOCAL_SPARK_CONFIG;
if( partitioner == PDataPartitioner.REMOTE_SPARK || mode == PExecMode.REMOTE_SPARK) {
DMLScript.USE_LOCAL_SPARK_CONFIG = true;
rtplatform = ExecMode.HYBRID;
}
try
{
//inst exec type, influenced via rows
int rows = small ? rows1 : rows2;
int cols = small ? cols1 : cols2;
//script
int scriptNum = -1;
switch( partitioner )
{
case NONE:
scriptNum=1;
break;
case LOCAL:
if( mode==PExecMode.LOCAL )
scriptNum=2;
else
scriptNum=3;
break;
case REMOTE_SPARK:
if( mode==PExecMode.LOCAL ){
if( !multiParts )
scriptNum = 7;
else
scriptNum = 9;
}
else
scriptNum = 8;
break;
default:
//do nothing
}
TestConfiguration config = getTestConfiguration(TEST_NAME);
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;
fullDMLScriptName = HOME + TEST_NAME + scriptNum + ".dml";
programArgs = new String[]{"-args", input("V"),
Integer.toString(rows), Integer.toString(cols), output("R") };
fullRScriptName = HOME + TEST_NAME + (multiParts?"6":"") + ".R";
rCmd = "Rscript" + " " + fullRScriptName + " " + inputDir() + " " + expectedDir();
long seed = System.nanoTime();
double sparsity = -1;
if( sparse )
sparsity = sparsity2;
else
sparsity = sparsity1;
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");
}
finally
{
rtplatform = oldRT;
DMLScript.USE_LOCAL_SPARK_CONFIG = oldUseSparkConfig;
}
}
}