/**
* @param testname
* @param sparse
* @param rewrites
* @param rep
* @param instType
*/
private void runWeightedCrossEntropyTest(
String testname, boolean sparse, boolean rewrites, boolean rep, ExecType instType) {
RUNTIME_PLATFORM platformOld = rtplatform;
switch (instType) {
case MR:
rtplatform = RUNTIME_PLATFORM.HADOOP;
break;
case SPARK:
rtplatform = RUNTIME_PLATFORM.SPARK;
break;
default:
rtplatform = RUNTIME_PLATFORM.HYBRID;
break;
}
boolean sparkConfigOld = DMLScript.USE_LOCAL_SPARK_CONFIG;
if (rtplatform == RUNTIME_PLATFORM.SPARK) DMLScript.USE_LOCAL_SPARK_CONFIG = true;
boolean rewritesOld = OptimizerUtils.ALLOW_ALGEBRAIC_SIMPLIFICATION;
boolean forceOld = QuaternaryOp.FORCE_REPLICATION;
OptimizerUtils.ALLOW_ALGEBRAIC_SIMPLIFICATION = rewrites;
QuaternaryOp.FORCE_REPLICATION = rep;
try {
double sparsity = (sparse) ? spSparse : spDense;
String TEST_NAME = testname;
TestConfiguration config = getTestConfiguration(TEST_NAME);
// 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[] {
"-stats",
"-explain",
"runtime",
"-args",
HOME + INPUT_DIR + "X",
HOME + INPUT_DIR + "U",
HOME + INPUT_DIR + "V",
HOME + OUTPUT_DIR + "R"
};
fullRScriptName = HOME + TEST_NAME + ".R";
rCmd = "Rscript" + " " + fullRScriptName + " " + HOME + INPUT_DIR + " " + HOME + EXPECTED_DIR;
loadTestConfiguration(config);
// generate actual dataset
double[][] X = getRandomMatrix(rows, cols, 0, 1, sparsity, 7);
writeInputMatrixWithMTD("X", X, true);
double[][] U = getRandomMatrix(rows, rank, 0, 1, 1.0, 678);
writeInputMatrixWithMTD("U", U, true);
double[][] V = getRandomMatrix(cols, rank, 0, 1, 1.0, 912);
writeInputMatrixWithMTD("V", V, true);
// run the scripts
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, "Stat-DML", "Stat-R");
checkDMLMetaDataFile("R", new MatrixCharacteristics(1, 1, 1, 1));
// check statistics for right operator in cp
if (instType == ExecType.CP && rewrites)
Assert.assertTrue(
"Missing opcode wcemm",
Statistics.getCPHeavyHitterOpCodes().contains(WeightedCrossEntropy.OPCODE_CP));
else if (instType == ExecType.SPARK && rewrites) {
Assert.assertTrue(
"Missing opcode sp_wcemm",
!rep
&& Statistics.getCPHeavyHitterOpCodes()
.contains(Instruction.SP_INST_PREFIX + WeightedCrossEntropy.OPCODE)
|| rep
&& Statistics.getCPHeavyHitterOpCodes()
.contains(Instruction.SP_INST_PREFIX + WeightedCrossEntropyR.OPCODE));
}
} finally {
rtplatform = platformOld;
DMLScript.USE_LOCAL_SPARK_CONFIG = sparkConfigOld;
OptimizerUtils.ALLOW_ALGEBRAIC_SIMPLIFICATION = rewritesOld;
QuaternaryOp.FORCE_REPLICATION = forceOld;
}
}
@Override
public void setUp() {
TestUtils.clearAssertionInformation();
addTestConfiguration(TEST_NAME, new TestConfiguration(TEST_DIR, TEST_NAME, new String[] {"R"}));
}
/**
* @param sparseM1
* @param sparseM2
* @param instType
*/
private void runColAggregateOperationTest(
OpType type, boolean sparse, boolean vector, ExecType instType, boolean rewrites) {
RUNTIME_PLATFORM platformOld = rtplatform;
switch (instType) {
case MR:
rtplatform = RUNTIME_PLATFORM.HADOOP;
break;
case SPARK:
rtplatform = RUNTIME_PLATFORM.SPARK;
break;
default:
rtplatform = RUNTIME_PLATFORM.HYBRID;
break;
}
boolean sparkConfigOld = DMLScript.USE_LOCAL_SPARK_CONFIG;
if (rtplatform == RUNTIME_PLATFORM.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;
getAndLoadTestConfiguration(TEST_NAME);
/* 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 = readDMLMatrixFromHDFS("B");
HashMap<CellIndex, Double> rfile = readRMatrixFromFS("B");
TestUtils.compareMatrices(dmlfile, rfile, eps, "Stat-DML", "Stat-R");
} finally {
rtplatform = platformOld;
DMLScript.USE_LOCAL_SPARK_CONFIG = sparkConfigOld;
OptimizerUtils.ALLOW_ALGEBRAIC_SIMPLIFICATION = oldRewritesFlag;
}
}
@AfterClass
public static void cleanUp() {
if (TEST_CACHE_ENABLED) {
TestUtils.clearDirectory(TEST_DATA_DIR + TEST_CLASS_DIR);
}
}
@BeforeClass
public static void init() {
TestUtils.clearDirectory(TEST_DATA_DIR + TEST_CLASS_DIR);
}
/**
* @param sparseM1
* @param sparseM2
* @param instType
*/
private void runMinMaxComparisonTest(
OpType type,
DataType dtM1,
DataType dtM2,
boolean sparseM1,
boolean sparseM2,
ExecType instType) {
// rtplatform for MR
RUNTIME_PLATFORM platformOld = rtplatform;
rtplatform = (instType == ExecType.MR) ? RUNTIME_PLATFORM.HADOOP : RUNTIME_PLATFORM.HYBRID;
// get the testname
String TEST_NAME = null;
int minFlag = (type == OpType.MIN) ? 1 : 0;
boolean s1Flag = (dtM1 == DataType.SCALAR);
boolean s2Flag = (dtM2 == DataType.SCALAR);
if (s1Flag && s2Flag) TEST_NAME = TEST_NAME4;
else if (s1Flag) TEST_NAME = TEST_NAME2;
else if (s2Flag) TEST_NAME = TEST_NAME3;
else TEST_NAME = TEST_NAME1;
String TEST_CACHE_DIR = "";
if (TEST_CACHE_ENABLED) {
int mrows1 = (dtM1 == DataType.MATRIX) ? rows : 1;
int mrows2 = (dtM2 == DataType.MATRIX) ? rows : 1;
double sparsityLeft = sparseM1 ? sparsity2 : sparsity1;
double sparsityRight = sparseM2 ? sparsity2 : sparsity1;
TEST_CACHE_DIR =
minFlag + "_" + mrows1 + "_" + mrows2 + "_" + sparsityLeft + "_" + sparsityRight + "/";
}
try {
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[] {
"-explain", "-args", input("A"), input("B"), Integer.toString(minFlag), output("C")
};
fullRScriptName = HOME + TEST_NAME_R + ".R";
rCmd =
"Rscript"
+ " "
+ fullRScriptName
+ " "
+ inputDir()
+ " "
+ minFlag
+ " "
+ expectedDir();
// generate actual dataset
int mrows1 = (dtM1 == DataType.MATRIX) ? rows : 1;
int mcols1 = (dtM1 == DataType.MATRIX) ? cols : 1;
int mrows2 = (dtM2 == DataType.MATRIX) ? rows : 1;
int mcols2 = (dtM2 == DataType.MATRIX) ? cols : 1;
double[][] A = getRandomMatrix(mrows1, mcols1, -1, 1, sparseM1 ? sparsity2 : sparsity1, 7);
writeInputMatrix("A", A, true);
MatrixCharacteristics mc1 = new MatrixCharacteristics(mrows1, mcols1, 1000, 1000);
MapReduceTool.writeMetaDataFile(
input("A.mtd"), ValueType.DOUBLE, mc1, OutputInfo.TextCellOutputInfo);
double[][] B = getRandomMatrix(mrows2, mcols2, -1, 1, sparseM2 ? sparsity2 : sparsity1, 3);
writeInputMatrix("B", B, true);
MatrixCharacteristics mc2 = new MatrixCharacteristics(mrows2, mcols2, 1000, 1000);
MapReduceTool.writeMetaDataFile(
input("B.mtd"), ValueType.DOUBLE, mc2, OutputInfo.TextCellOutputInfo);
// run test
runTest(true, false, null, -1);
runRScript(true);
// compare matrices
HashMap<CellIndex, Double> dmlfile = readDMLMatrixFromHDFS("C");
HashMap<CellIndex, Double> rfile = readRMatrixFromFS("C");
TestUtils.compareMatrices(dmlfile, rfile, eps, "Stat-DML", "Stat-R");
} catch (IOException e) {
e.printStackTrace();
throw new RuntimeException(e);
} finally {
rtplatform = platformOld;
}
}
/**
* @param sparseM1
* @param sparseM2
* @param instType
*/
private void runGDFOTest(String testname, boolean sparse, ExecType instType) {
// rtplatform for MR
RUNTIME_PLATFORM platformOld = rtplatform;
switch (instType) {
case MR:
rtplatform = RUNTIME_PLATFORM.HADOOP;
break;
case SPARK:
rtplatform = RUNTIME_PLATFORM.SPARK;
break;
default:
rtplatform = RUNTIME_PLATFORM.HYBRID;
break;
}
boolean sparkConfigOld = DMLScript.USE_LOCAL_SPARK_CONFIG;
if (rtplatform == RUNTIME_PLATFORM.SPARK) DMLScript.USE_LOCAL_SPARK_CONFIG = true;
try {
String TEST_NAME = testname;
TestConfiguration config = getTestConfiguration(TEST_NAME);
/* 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[] {
"-explain", // "hops",
"-config=" + HOME + TEST_CONF,
"-args",
HOME + INPUT_DIR + "X",
HOME + INPUT_DIR + "y",
String.valueOf(intercept),
String.valueOf(epsilon),
String.valueOf(maxiter),
HOME + OUTPUT_DIR + "w"
};
fullRScriptName = HOME + TEST_NAME + ".R";
rCmd =
"Rscript"
+ " "
+ fullRScriptName
+ " "
+ HOME
+ INPUT_DIR
+ " "
+ String.valueOf(intercept)
+ " "
+ String.valueOf(epsilon)
+ " "
+ String.valueOf(maxiter)
+ " "
+ HOME
+ EXPECTED_DIR;
loadTestConfiguration(config);
// generate actual datasets
double[][] X = getRandomMatrix(rows, cols, 0, 1, sparse ? sparsity2 : sparsity1, 7);
writeInputMatrixWithMTD("X", X, true);
double[][] y = getRandomMatrix(rows, 1, 0, 10, 1.0, 3);
writeInputMatrixWithMTD("y", y, true);
runTest(true, false, null, -1);
runRScript(true);
// compare matrices
HashMap<CellIndex, Double> dmlfile = readDMLMatrixFromHDFS("w");
HashMap<CellIndex, Double> rfile = readRMatrixFromFS("w");
TestUtils.compareMatrices(dmlfile, rfile, eps, "Stat-DML", "Stat-R");
} finally {
rtplatform = platformOld;
DMLScript.USE_LOCAL_SPARK_CONFIG = sparkConfigOld;
}
}