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* to you under the Apache License, Version 2.0 (the
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*
* http://www.apache.org/licenses/LICENSE-2.0
*
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package org.apache.sysds.test.functions.parfor.partition;
import java.util.HashMap;
import org.junit.Assert;
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.controlprogram.parfor.stat.InfrastructureAnalyzer;
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 ParForDataPartitionExecuteTest extends AutomatedTestBase
{
private final static String TEST_NAME = "DataPartitionExecute";
private final static String TEST_DIR = "functions/parfor/";
private final static String TEST_CLASS_DIR = TEST_DIR + ParForDataPartitionExecuteTest.class.getSimpleName() + "/";
private final static double eps = 1e-10;
private final static int dim1 = 2001;
private final static int dim2 = 101;
private final static double sparsity1 = 0.7;
private final static double sparsity2 = 0.3d;
@Override
public void setUp() {
addTestConfiguration(TEST_NAME, new TestConfiguration(TEST_CLASS_DIR, TEST_NAME, new String[]{"R"}));
}
@Test
public void testFusedDataPartitionExecuteRowDenseSpark() {
runFusedDataPartitionExecuteTest(false, true, ExecType.SPARK);
}
@Test
public void testFusedDataPartitionExecuteColDenseSpark() {
runFusedDataPartitionExecuteTest(false, false, ExecType.SPARK);
}
@Test
public void testFusedDataPartitionExecuteRowSparseSpark() {
runFusedDataPartitionExecuteTest(true, true, ExecType.SPARK);
}
@Test
public void testFusedDataPartitionExecuteColSparseSpark() {
runFusedDataPartitionExecuteTest(true, false, ExecType.SPARK);
}
private void runFusedDataPartitionExecuteTest(boolean sparse, boolean row, ExecType et)
{
ExecMode platformOld = rtplatform;
switch( et ){
case SPARK: rtplatform = ExecMode.HYBRID; break;
default: throw new RuntimeException("Unsupported exec type: "+et.name());
}
boolean sparkConfigOld = DMLScript.USE_LOCAL_SPARK_CONFIG;
if( et == ExecType.SPARK )
DMLScript.USE_LOCAL_SPARK_CONFIG = true;
//modify memory budget to trigger fused datapartition-execute
long oldmem = InfrastructureAnalyzer.getLocalMaxMemory();
InfrastructureAnalyzer.setLocalMaxMemory(1*1024*1024); //1MB
try
{
int rows = row ? dim2 : dim1;
int cols = row ? dim1 : dim2;
TestConfiguration config = getTestConfiguration(TEST_NAME);
config.addVariable("rows", rows);
config.addVariable("cols", cols);
loadTestConfiguration(config);
String HOME = SCRIPT_DIR + TEST_DIR;
fullDMLScriptName = HOME + TEST_NAME + ".dml";
programArgs = new String[]{"-stats", "-args", input("X"),
String.valueOf(et == ExecType.SPARK).toUpperCase(),
String.valueOf(row).toUpperCase(), output("R") };
fullRScriptName = HOME + TEST_NAME + ".R";
rCmd = "Rscript" + " " + fullRScriptName + " " + inputDir()
+ " " + String.valueOf(row).toUpperCase() + " " + expectedDir();
//generate input data
double sparsity = sparse ? sparsity2 : sparsity1;
double[][] X = getRandomMatrix(rows, cols, 0, 1, sparsity, 7);
writeInputMatrixWithMTD("X", X, true);
//run test case
runTest(true, false, null, -1);
runRScript(true);
//compare matrices
HashMap<CellIndex, Double> dmlfile = readDMLMatrixFromHDFS("R");
HashMap<CellIndex, Double> rfile = readRMatrixFromFS("R");
TestUtils.compareMatrices(dmlfile, rfile, eps, "DML", "R");
//check for compiled datapartition-execute
Assert.assertTrue(heavyHittersContainsSubString(
(et == ExecType.SPARK) ? "ParFor-DPESP" : "MR-Job_ParFor-DPEMR"));
}
finally {
rtplatform = platformOld;
DMLScript.USE_LOCAL_SPARK_CONFIG = sparkConfigOld;
InfrastructureAnalyzer.setLocalMaxMemory(oldmem); //1MB
}
}
}