src/test/java/org/apache/sysds/test/functions/privacy/FederatedWorkerHandlerTest.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.privacy;

 import java.util.Arrays;

 import org.apache.sysds.api.DMLException;
 import org.apache.sysds.api.DMLScript;
 import org.apache.sysds.runtime.meta.MatrixCharacteristics;
 import org.apache.sysds.runtime.privacy.PrivacyConstraint;
 import org.apache.sysds.runtime.privacy.PrivacyConstraint.PrivacyLevel;
 import org.apache.sysds.test.AutomatedTestBase;
 import org.apache.sysds.test.TestConfiguration;
 import org.apache.sysds.test.TestUtils;
 import org.junit.Ignore;
 import org.junit.Test;
 import org.apache.sysds.common.Types;
 import static java.lang.Thread.sleep;

 @net.jcip.annotations.NotThreadSafe
 @Ignore //FIXME: fix privacy propagation for various operations
 public class FederatedWorkerHandlerTest extends AutomatedTestBase {

 	private static final String TEST_DIR = "functions/federated/";
 	private static final String TEST_DIR_SCALAR = TEST_DIR + "matrix_scalar/";
 	private final static String TEST_CLASS_DIR = TEST_DIR + FederatedWorkerHandlerTest.class.getSimpleName() + "/";
 	private final static String TEST_CLASS_DIR_SCALAR = TEST_DIR_SCALAR + FederatedWorkerHandlerTest.class.getSimpleName() + "/";
 	private static final String TEST_PROG_SCALAR_ADDITION_MATRIX = "ScalarAdditionFederatedMatrix";
 	private final static String AGGREGATION_TEST_NAME = "FederatedSumTest";
 	private final static String TRANSFER_TEST_NAME = "FederatedRCBindTest";
 	private final static String MATVECMULT_TEST_NAME = "FederatedMultiplyTest";
 	private static final String FEDERATED_WORKER_HOST = "localhost";
 	private static final int FEDERATED_WORKER_PORT = 1222;

 	private final static int blocksize = 1024;
 	private final int rows = 10;
 	private final int cols = 10;

 	@Override
 	public void setUp() {
 		TestUtils.clearAssertionInformation();
 		addTestConfiguration("scalar", new TestConfiguration(TEST_CLASS_DIR_SCALAR, TEST_PROG_SCALAR_ADDITION_MATRIX, new String [] {"R"}));
 		addTestConfiguration("aggregation", new TestConfiguration(TEST_CLASS_DIR, AGGREGATION_TEST_NAME, new String[] {"S.scalar", "R", "C"}));
 		addTestConfiguration("transfer", new TestConfiguration(TEST_CLASS_DIR, TRANSFER_TEST_NAME, new String[] {"R", "C"}));
 		addTestConfiguration("matvecmult", new TestConfiguration(TEST_CLASS_DIR, MATVECMULT_TEST_NAME, new String[] {"Z"}));
 	}

 	@Test
 	public void scalarPrivateTest(){
 		scalarTest(PrivacyLevel.Private, DMLException.class);
 	}

 	@Test
 	public void scalarPrivateAggregationTest(){
 		scalarTest(PrivacyLevel.PrivateAggregation, DMLException.class);
 	}

 	@Test
 	public void scalarNonePrivateTest(){
 		scalarTest(PrivacyLevel.None, null);
 	}

 	private void scalarTest(PrivacyLevel privacyLevel, Class<?> expectedException){
 		getAndLoadTestConfiguration("scalar");

 		double[][] m = getRandomMatrix(this.rows, this.cols, -1, 1, 1.0, 1);

 		PrivacyConstraint pc = new PrivacyConstraint(privacyLevel);
 		writeInputMatrixWithMTD("M", m, false, new MatrixCharacteristics(rows, cols, blocksize, rows * cols), pc);

 		int s = TestUtils.getRandomInt();
 		double[][] r = new double[rows][cols];
 		for(int i = 0; i < rows; i++) {
 			for(int j = 0; j < cols; j++) {
 				r[i][j] = m[i][j] + s;
 			}
 		}
 		if (expectedException == null)
 			writeExpectedMatrix("R", r);

 		runGenericScalarTest(TEST_PROG_SCALAR_ADDITION_MATRIX, s, expectedException, privacyLevel);
 	}


 	private void runGenericScalarTest(String dmlFile, int s, Class<?> expectedException, PrivacyLevel privacyLevel)
 	{
 		boolean sparkConfigOld = DMLScript.USE_LOCAL_SPARK_CONFIG;
 		Types.ExecMode platformOld = rtplatform;

 		Thread t = null;
 		try {
 			// we need the reference file to not be written to hdfs, so we get the correct format
 			rtplatform = Types.ExecMode.SINGLE_NODE;
 			programArgs = new String[] {"-w", Integer.toString(FEDERATED_WORKER_PORT)};
 			t = new Thread(() -> runTest(true, false, null, -1));
 			t.start();
 			sleep(FED_WORKER_WAIT);
 			fullDMLScriptName = SCRIPT_DIR + TEST_DIR_SCALAR + dmlFile + ".dml";
 			programArgs = new String[]{"-checkPrivacy", "-args",
 					TestUtils.federatedAddress(FEDERATED_WORKER_HOST, FEDERATED_WORKER_PORT, input("M")),
 					Integer.toString(rows), Integer.toString(cols),
 					Integer.toString(s),
 					output("R")};
 			boolean exceptionExpected = (expectedException != null);
 			runTest(true, exceptionExpected, expectedException, -1);

 			if ( !exceptionExpected )
 				compareResults();
 		} catch (InterruptedException e) {
 			e.printStackTrace();
 			assert (false);
 		} finally {
 			assert(checkedPrivacyConstraintsContains(privacyLevel));
 			rtplatform = platformOld;
 			TestUtils.shutdownThread(t);
 			rtplatform = platformOld;
 			DMLScript.USE_LOCAL_SPARK_CONFIG = sparkConfigOld;
 		}
 	}

 	@Test
 	public void aggregatePrivateTest() {
 		federatedSum(Types.ExecMode.SINGLE_NODE, PrivacyLevel.Private, DMLException.class);
 	}

 	@Test
 	public void aggregatePrivateAggregationTest() {
 		federatedSum(Types.ExecMode.SINGLE_NODE, PrivacyLevel.PrivateAggregation, null);
 	}

 	@Test
 	public void aggregateNonePrivateTest() {
 		federatedSum(Types.ExecMode.SINGLE_NODE, PrivacyLevel.None, null);
 	}

 	public void federatedSum(Types.ExecMode execMode, PrivacyLevel privacyLevel, Class<?> expectedException) {
 		boolean sparkConfigOld = DMLScript.USE_LOCAL_SPARK_CONFIG;
 		Types.ExecMode platformOld = rtplatform;

 		Thread t;

 		getAndLoadTestConfiguration("aggregation");
 		String HOME = SCRIPT_DIR + TEST_DIR;

 		double[][] A = getRandomMatrix(rows, cols, -10, 10, 1, 1);
 		writeInputMatrixWithMTD("A", A, false, new MatrixCharacteristics(rows, cols, blocksize, rows * cols), new PrivacyConstraint(privacyLevel));
 		int port = getRandomAvailablePort();
 		t = startLocalFedWorker(port);

 		// we need the reference file to not be written to hdfs, so we get the correct format
 		rtplatform = Types.ExecMode.SINGLE_NODE;
 		// Run reference dml script with normal matrix for Row/Col sum
 		fullDMLScriptName = HOME + AGGREGATION_TEST_NAME + "Reference.dml";
 		programArgs = new String[] {"-args", input("A"), input("A"), expected("R"), expected("C")};
 		runTest(true, false, null, -1);

 		// write expected sum
 		double sum = 0;
 		for(double[] doubles : A) {
 			sum += Arrays.stream(doubles).sum();
 		}
 		sum *= 2;

 		if ( expectedException == null )
 			writeExpectedScalar("S", sum);

 		// reference file should not be written to hdfs, so we set platform here
 		rtplatform = execMode;
 		if(rtplatform == Types.ExecMode.SPARK) {
 			DMLScript.USE_LOCAL_SPARK_CONFIG = true;
 		}
 		TestConfiguration config = availableTestConfigurations.get("aggregation");
 		loadTestConfiguration(config);
 		fullDMLScriptName = HOME + AGGREGATION_TEST_NAME + ".dml";
 		programArgs = new String[] {"-checkPrivacy", "-args", "\"localhost:" + port + "/" + input("A") + "\"", Integer.toString(rows),
 			Integer.toString(cols), Integer.toString(rows * 2), output("S"), output("R"), output("C")};

 		runTest(true, (expectedException != null), expectedException, -1);

 		// compare all sums via files
 		if ( expectedException == null )
 			compareResults(1e-11);

 		assert(checkedPrivacyConstraintsContains(privacyLevel));

 		TestUtils.shutdownThread(t);
 		rtplatform = platformOld;
 		DMLScript.USE_LOCAL_SPARK_CONFIG = sparkConfigOld;
 	}

 	@Test
 	public void transferPrivateTest() {
 		federatedRCBind(Types.ExecMode.SINGLE_NODE, PrivacyLevel.Private, DMLException.class);
 	}

 	@Test
 	public void transferPrivateAggregationTest() {
 		federatedRCBind(Types.ExecMode.SINGLE_NODE, PrivacyLevel.PrivateAggregation, DMLException.class);
 	}

 	@Test
 	public void transferNonePrivateTest() {
 		federatedRCBind(Types.ExecMode.SINGLE_NODE, PrivacyLevel.None, null);
 	}

 	public void federatedRCBind(Types.ExecMode execMode, PrivacyLevel privacyLevel, Class<?> expectedException) {
 		boolean sparkConfigOld = DMLScript.USE_LOCAL_SPARK_CONFIG;
 		Types.ExecMode platformOld = rtplatform;

 		Thread t;

 		getAndLoadTestConfiguration("transfer");
 		String HOME = SCRIPT_DIR + TEST_DIR;

 		double[][] A = getRandomMatrix(rows, cols, -10, 10, 1, 1);
 		writeInputMatrixWithMTD("A", A, false, new MatrixCharacteristics(rows, cols, blocksize, rows * cols), new PrivacyConstraint(privacyLevel));

 		int port = getRandomAvailablePort();
 		t = startLocalFedWorker(port);

 		// we need the reference file to not be written to hdfs, so we get the correct format
 		rtplatform = Types.ExecMode.SINGLE_NODE;
 		// Run reference dml script with normal matrix for Row/Col sum
 		fullDMLScriptName = HOME + TRANSFER_TEST_NAME + "Reference.dml";
 		programArgs = new String[] {"-checkPrivacy", "-args", input("A"), expected("R"), expected("C")};
 		runTest(true, false, null, -1);

 		// reference file should not be written to hdfs, so we set platform here
 		rtplatform = execMode;
 		if(rtplatform == Types.ExecMode.SPARK) {
 			DMLScript.USE_LOCAL_SPARK_CONFIG = true;
 		}
 		TestConfiguration config = availableTestConfigurations.get("transfer");
 		loadTestConfiguration(config);
 		fullDMLScriptName = HOME + TRANSFER_TEST_NAME + ".dml";
 		programArgs = new String[] {"-checkPrivacy", "-args", "\"localhost:" + port + "/" + input("A") + "\"", Integer.toString(rows),
 			Integer.toString(cols), output("R"), output("C")};

 		runTest(true, (expectedException != null), expectedException, -1);

 		// compare all sums via files
 		if ( expectedException == null )
 			compareResults(1e-11);

 		assert(checkedPrivacyConstraintsContains(privacyLevel));

 		TestUtils.shutdownThread(t);
 		rtplatform = platformOld;
 		DMLScript.USE_LOCAL_SPARK_CONFIG = sparkConfigOld;
 	}

 	@Test
 	public void matVecMultPrivateTest() {
 		federatedMultiply(Types.ExecMode.SINGLE_NODE, PrivacyLevel.Private, DMLException.class);
 	}

 	@Test
 	public void matVecMultPrivateAggregationTest() {
 		federatedMultiply(Types.ExecMode.SINGLE_NODE, PrivacyLevel.PrivateAggregation, DMLException.class);
 	}

 	@Test
 	public void matVecMultNonePrivateTest() {
 		federatedMultiply(Types.ExecMode.SINGLE_NODE, PrivacyLevel.None, null);
 	}

 	public void federatedMultiply(Types.ExecMode execMode, PrivacyLevel privacyLevel, Class<?> expectedException) {
 		boolean sparkConfigOld = DMLScript.USE_LOCAL_SPARK_CONFIG;
 		Types.ExecMode platformOld = rtplatform;
 		rtplatform = execMode;
 		if(rtplatform == Types.ExecMode.SPARK) {
 			DMLScript.USE_LOCAL_SPARK_CONFIG = true;
 		}

 		Thread t1, t2;

 		getAndLoadTestConfiguration("matvecmult");
 		String HOME = SCRIPT_DIR + TEST_DIR;

 		// write input matrices
 		int halfRows = rows / 2;
 		// We have two matrices handled by a single federated worker
 		double[][] X1 = getRandomMatrix(halfRows, cols, 0, 1, 1, 42);
 		double[][] X2 = getRandomMatrix(halfRows, cols, 0, 1, 1, 1340);
 		// And another two matrices handled by a single federated worker
 		double[][] Y1 = getRandomMatrix(cols, halfRows, 0, 1, 1, 44);
 		double[][] Y2 = getRandomMatrix(cols, halfRows, 0, 1, 1, 21);

 		writeInputMatrixWithMTD("X1", X1, false, new MatrixCharacteristics(halfRows, cols, blocksize, halfRows * cols), new PrivacyConstraint(privacyLevel));
 		writeInputMatrixWithMTD("X2", X2, false, new MatrixCharacteristics(halfRows, cols, blocksize, halfRows * cols));
 		writeInputMatrixWithMTD("Y1", Y1, false, new MatrixCharacteristics(cols, halfRows, blocksize, halfRows * cols));
 		writeInputMatrixWithMTD("Y2", Y2, false, new MatrixCharacteristics(cols, halfRows, blocksize, halfRows * cols));

 		int port1 = getRandomAvailablePort();
 		int port2 = getRandomAvailablePort();
 		t1 = startLocalFedWorker(port1);
 		t2 = startLocalFedWorker(port2);

 		TestConfiguration config = availableTestConfigurations.get("matvecmult");
 		loadTestConfiguration(config);

 		// Run reference dml script with normal matrix
 		fullDMLScriptName = HOME + MATVECMULT_TEST_NAME + "Reference.dml";
 		programArgs = new String[] {"-nvargs", "X1=" + input("X1"), "X2=" + input("X2"), "Y1=" + input("Y1"),
 			"Y2=" + input("Y2"), "Z=" + expected("Z")};
 		runTest(true, false, null, -1);

 		// Run actual dml script with federated matrix
 		fullDMLScriptName = HOME + MATVECMULT_TEST_NAME + ".dml";
 		programArgs = new String[] {"-checkPrivacy",
 			"-nvargs",
 			"X1=" + TestUtils.federatedAddress(port1, input("X1")),
 			"X2=" + TestUtils.federatedAddress(port2, input("X2")),
 			"Y1=" + TestUtils.federatedAddress(port1, input("Y1")),
 			"Y2=" + TestUtils.federatedAddress(port2, input("Y2")), "r=" + rows, "c=" + cols,
 			"hr=" + halfRows, "Z=" + output("Z")};
 		runTest(true, (expectedException != null), expectedException, -1);

 		// compare via files
 		if (expectedException == null)
 			compareResults(1e-9);

 		assert(checkedPrivacyConstraintsContains(privacyLevel));

 		TestUtils.shutdownThreads(t1, t2);

 		rtplatform = platformOld;
 		DMLScript.USE_LOCAL_SPARK_CONFIG = sparkConfigOld;
 	}
 }
	/*
	* 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.privacy;

	import java.util.Arrays;

	import org.apache.sysds.api.DMLException;
	import org.apache.sysds.api.DMLScript;
	import org.apache.sysds.runtime.meta.MatrixCharacteristics;
	import org.apache.sysds.runtime.privacy.PrivacyConstraint;
	import org.apache.sysds.runtime.privacy.PrivacyConstraint.PrivacyLevel;
	import org.apache.sysds.test.AutomatedTestBase;
	import org.apache.sysds.test.TestConfiguration;
	import org.apache.sysds.test.TestUtils;
	import org.junit.Ignore;
	import org.junit.Test;
	import org.apache.sysds.common.Types;
	import static java.lang.Thread.sleep;

	@net.jcip.annotations.NotThreadSafe
	@Ignore //FIXME: fix privacy propagation for various operations
	public class FederatedWorkerHandlerTest extends AutomatedTestBase {

	private static final String TEST_DIR = "functions/federated/";
	private static final String TEST_DIR_SCALAR = TEST_DIR + "matrix_scalar/";
	private final static String TEST_CLASS_DIR = TEST_DIR + FederatedWorkerHandlerTest.class.getSimpleName() + "/";
	private final static String TEST_CLASS_DIR_SCALAR = TEST_DIR_SCALAR + FederatedWorkerHandlerTest.class.getSimpleName() + "/";
	private static final String TEST_PROG_SCALAR_ADDITION_MATRIX = "ScalarAdditionFederatedMatrix";
	private final static String AGGREGATION_TEST_NAME = "FederatedSumTest";
	private final static String TRANSFER_TEST_NAME = "FederatedRCBindTest";
	private final static String MATVECMULT_TEST_NAME = "FederatedMultiplyTest";
	private static final String FEDERATED_WORKER_HOST = "localhost";
	private static final int FEDERATED_WORKER_PORT = 1222;

	private final static int blocksize = 1024;
	private final int rows = 10;
	private final int cols = 10;

	@Override
	public void setUp() {
	TestUtils.clearAssertionInformation();
	addTestConfiguration("scalar", new TestConfiguration(TEST_CLASS_DIR_SCALAR, TEST_PROG_SCALAR_ADDITION_MATRIX, new String [] {"R"}));
	addTestConfiguration("aggregation", new TestConfiguration(TEST_CLASS_DIR, AGGREGATION_TEST_NAME, new String[] {"S.scalar", "R", "C"}));
	addTestConfiguration("transfer", new TestConfiguration(TEST_CLASS_DIR, TRANSFER_TEST_NAME, new String[] {"R", "C"}));
	addTestConfiguration("matvecmult", new TestConfiguration(TEST_CLASS_DIR, MATVECMULT_TEST_NAME, new String[] {"Z"}));
	}

	@Test
	public void scalarPrivateTest(){
	scalarTest(PrivacyLevel.Private, DMLException.class);
	}

	@Test
	public void scalarPrivateAggregationTest(){
	scalarTest(PrivacyLevel.PrivateAggregation, DMLException.class);
	}

	@Test
	public void scalarNonePrivateTest(){
	scalarTest(PrivacyLevel.None, null);
	}

	private void scalarTest(PrivacyLevel privacyLevel, Class<?> expectedException){
	getAndLoadTestConfiguration("scalar");

	double[][] m = getRandomMatrix(this.rows, this.cols, -1, 1, 1.0, 1);

	PrivacyConstraint pc = new PrivacyConstraint(privacyLevel);
	writeInputMatrixWithMTD("M", m, false, new MatrixCharacteristics(rows, cols, blocksize, rows * cols), pc);

	int s = TestUtils.getRandomInt();
	double[][] r = new double[rows][cols];
	for(int i = 0; i < rows; i++) {
	for(int j = 0; j < cols; j++) {
	r[i][j] = m[i][j] + s;
	}
	}
	if (expectedException == null)
	writeExpectedMatrix("R", r);

	runGenericScalarTest(TEST_PROG_SCALAR_ADDITION_MATRIX, s, expectedException, privacyLevel);
	}


	private void runGenericScalarTest(String dmlFile, int s, Class<?> expectedException, PrivacyLevel privacyLevel)
	{
	boolean sparkConfigOld = DMLScript.USE_LOCAL_SPARK_CONFIG;
	Types.ExecMode platformOld = rtplatform;

	Thread t = null;
	try {
	// we need the reference file to not be written to hdfs, so we get the correct format
	rtplatform = Types.ExecMode.SINGLE_NODE;
	programArgs = new String[] {"-w", Integer.toString(FEDERATED_WORKER_PORT)};
	t = new Thread(() -> runTest(true, false, null, -1));
	t.start();
	sleep(FED_WORKER_WAIT);
	fullDMLScriptName = SCRIPT_DIR + TEST_DIR_SCALAR + dmlFile + ".dml";
	programArgs = new String[]{"-checkPrivacy", "-args",
	TestUtils.federatedAddress(FEDERATED_WORKER_HOST, FEDERATED_WORKER_PORT, input("M")),
	Integer.toString(rows), Integer.toString(cols),
	Integer.toString(s),
	output("R")};
	boolean exceptionExpected = (expectedException != null);
	runTest(true, exceptionExpected, expectedException, -1);

	if ( !exceptionExpected )
	compareResults();
	} catch (InterruptedException e) {
	e.printStackTrace();
	assert (false);
	} finally {
	assert(checkedPrivacyConstraintsContains(privacyLevel));
	rtplatform = platformOld;
	TestUtils.shutdownThread(t);
	rtplatform = platformOld;
	DMLScript.USE_LOCAL_SPARK_CONFIG = sparkConfigOld;
	}
	}

	@Test
	public void aggregatePrivateTest() {
	federatedSum(Types.ExecMode.SINGLE_NODE, PrivacyLevel.Private, DMLException.class);
	}

	@Test
	public void aggregatePrivateAggregationTest() {
	federatedSum(Types.ExecMode.SINGLE_NODE, PrivacyLevel.PrivateAggregation, null);
	}

	@Test
	public void aggregateNonePrivateTest() {
	federatedSum(Types.ExecMode.SINGLE_NODE, PrivacyLevel.None, null);
	}

	public void federatedSum(Types.ExecMode execMode, PrivacyLevel privacyLevel, Class<?> expectedException) {
	boolean sparkConfigOld = DMLScript.USE_LOCAL_SPARK_CONFIG;
	Types.ExecMode platformOld = rtplatform;

	Thread t;

	getAndLoadTestConfiguration("aggregation");
	String HOME = SCRIPT_DIR + TEST_DIR;

	double[][] A = getRandomMatrix(rows, cols, -10, 10, 1, 1);
	writeInputMatrixWithMTD("A", A, false, new MatrixCharacteristics(rows, cols, blocksize, rows * cols), new PrivacyConstraint(privacyLevel));
	int port = getRandomAvailablePort();
	t = startLocalFedWorker(port);

	// we need the reference file to not be written to hdfs, so we get the correct format
	rtplatform = Types.ExecMode.SINGLE_NODE;
	// Run reference dml script with normal matrix for Row/Col sum
	fullDMLScriptName = HOME + AGGREGATION_TEST_NAME + "Reference.dml";
	programArgs = new String[] {"-args", input("A"), input("A"), expected("R"), expected("C")};
	runTest(true, false, null, -1);

	// write expected sum
	double sum = 0;
	for(double[] doubles : A) {
	sum += Arrays.stream(doubles).sum();
	}
	sum *= 2;

	if ( expectedException == null )
	writeExpectedScalar("S", sum);

	// reference file should not be written to hdfs, so we set platform here
	rtplatform = execMode;
	if(rtplatform == Types.ExecMode.SPARK) {
	DMLScript.USE_LOCAL_SPARK_CONFIG = true;
	}
	TestConfiguration config = availableTestConfigurations.get("aggregation");
	loadTestConfiguration(config);
	fullDMLScriptName = HOME + AGGREGATION_TEST_NAME + ".dml";
	programArgs = new String[] {"-checkPrivacy", "-args", "\"localhost:" + port + "/" + input("A") + "\"", Integer.toString(rows),
	Integer.toString(cols), Integer.toString(rows * 2), output("S"), output("R"), output("C")};

	runTest(true, (expectedException != null), expectedException, -1);

	// compare all sums via files
	if ( expectedException == null )
	compareResults(1e-11);

	assert(checkedPrivacyConstraintsContains(privacyLevel));

	TestUtils.shutdownThread(t);
	rtplatform = platformOld;
	DMLScript.USE_LOCAL_SPARK_CONFIG = sparkConfigOld;
	}

	@Test
	public void transferPrivateTest() {
	federatedRCBind(Types.ExecMode.SINGLE_NODE, PrivacyLevel.Private, DMLException.class);
	}

	@Test
	public void transferPrivateAggregationTest() {
	federatedRCBind(Types.ExecMode.SINGLE_NODE, PrivacyLevel.PrivateAggregation, DMLException.class);
	}

	@Test
	public void transferNonePrivateTest() {
	federatedRCBind(Types.ExecMode.SINGLE_NODE, PrivacyLevel.None, null);
	}

	public void federatedRCBind(Types.ExecMode execMode, PrivacyLevel privacyLevel, Class<?> expectedException) {
	boolean sparkConfigOld = DMLScript.USE_LOCAL_SPARK_CONFIG;
	Types.ExecMode platformOld = rtplatform;

	Thread t;

	getAndLoadTestConfiguration("transfer");
	String HOME = SCRIPT_DIR + TEST_DIR;

	double[][] A = getRandomMatrix(rows, cols, -10, 10, 1, 1);
	writeInputMatrixWithMTD("A", A, false, new MatrixCharacteristics(rows, cols, blocksize, rows * cols), new PrivacyConstraint(privacyLevel));

	int port = getRandomAvailablePort();
	t = startLocalFedWorker(port);

	// we need the reference file to not be written to hdfs, so we get the correct format
	rtplatform = Types.ExecMode.SINGLE_NODE;
	// Run reference dml script with normal matrix for Row/Col sum
	fullDMLScriptName = HOME + TRANSFER_TEST_NAME + "Reference.dml";
	programArgs = new String[] {"-checkPrivacy", "-args", input("A"), expected("R"), expected("C")};
	runTest(true, false, null, -1);

	// reference file should not be written to hdfs, so we set platform here
	rtplatform = execMode;
	if(rtplatform == Types.ExecMode.SPARK) {
	DMLScript.USE_LOCAL_SPARK_CONFIG = true;
	}
	TestConfiguration config = availableTestConfigurations.get("transfer");
	loadTestConfiguration(config);
	fullDMLScriptName = HOME + TRANSFER_TEST_NAME + ".dml";
	programArgs = new String[] {"-checkPrivacy", "-args", "\"localhost:" + port + "/" + input("A") + "\"", Integer.toString(rows),
	Integer.toString(cols), output("R"), output("C")};

	runTest(true, (expectedException != null), expectedException, -1);

	// compare all sums via files
	if ( expectedException == null )
	compareResults(1e-11);

	assert(checkedPrivacyConstraintsContains(privacyLevel));

	TestUtils.shutdownThread(t);
	rtplatform = platformOld;
	DMLScript.USE_LOCAL_SPARK_CONFIG = sparkConfigOld;
	}

	@Test
	public void matVecMultPrivateTest() {
	federatedMultiply(Types.ExecMode.SINGLE_NODE, PrivacyLevel.Private, DMLException.class);
	}

	@Test
	public void matVecMultPrivateAggregationTest() {
	federatedMultiply(Types.ExecMode.SINGLE_NODE, PrivacyLevel.PrivateAggregation, DMLException.class);
	}

	@Test
	public void matVecMultNonePrivateTest() {
	federatedMultiply(Types.ExecMode.SINGLE_NODE, PrivacyLevel.None, null);
	}

	public void federatedMultiply(Types.ExecMode execMode, PrivacyLevel privacyLevel, Class<?> expectedException) {
	boolean sparkConfigOld = DMLScript.USE_LOCAL_SPARK_CONFIG;
	Types.ExecMode platformOld = rtplatform;
	rtplatform = execMode;
	if(rtplatform == Types.ExecMode.SPARK) {
	DMLScript.USE_LOCAL_SPARK_CONFIG = true;
	}

	Thread t1, t2;

	getAndLoadTestConfiguration("matvecmult");
	String HOME = SCRIPT_DIR + TEST_DIR;

	// write input matrices
	int halfRows = rows / 2;
	// We have two matrices handled by a single federated worker
	double[][] X1 = getRandomMatrix(halfRows, cols, 0, 1, 1, 42);
	double[][] X2 = getRandomMatrix(halfRows, cols, 0, 1, 1, 1340);
	// And another two matrices handled by a single federated worker
	double[][] Y1 = getRandomMatrix(cols, halfRows, 0, 1, 1, 44);
	double[][] Y2 = getRandomMatrix(cols, halfRows, 0, 1, 1, 21);

	writeInputMatrixWithMTD("X1", X1, false, new MatrixCharacteristics(halfRows, cols, blocksize, halfRows * cols), new PrivacyConstraint(privacyLevel));
	writeInputMatrixWithMTD("X2", X2, false, new MatrixCharacteristics(halfRows, cols, blocksize, halfRows * cols));
	writeInputMatrixWithMTD("Y1", Y1, false, new MatrixCharacteristics(cols, halfRows, blocksize, halfRows * cols));
	writeInputMatrixWithMTD("Y2", Y2, false, new MatrixCharacteristics(cols, halfRows, blocksize, halfRows * cols));

	int port1 = getRandomAvailablePort();
	int port2 = getRandomAvailablePort();
	t1 = startLocalFedWorker(port1);
	t2 = startLocalFedWorker(port2);

	TestConfiguration config = availableTestConfigurations.get("matvecmult");
	loadTestConfiguration(config);

	// Run reference dml script with normal matrix
	fullDMLScriptName = HOME + MATVECMULT_TEST_NAME + "Reference.dml";
	programArgs = new String[] {"-nvargs", "X1=" + input("X1"), "X2=" + input("X2"), "Y1=" + input("Y1"),
	"Y2=" + input("Y2"), "Z=" + expected("Z")};
	runTest(true, false, null, -1);

	// Run actual dml script with federated matrix
	fullDMLScriptName = HOME + MATVECMULT_TEST_NAME + ".dml";
	programArgs = new String[] {"-checkPrivacy",
	"-nvargs",
	"X1=" + TestUtils.federatedAddress(port1, input("X1")),
	"X2=" + TestUtils.federatedAddress(port2, input("X2")),
	"Y1=" + TestUtils.federatedAddress(port1, input("Y1")),
	"Y2=" + TestUtils.federatedAddress(port2, input("Y2")), "r=" + rows, "c=" + cols,
	"hr=" + halfRows, "Z=" + output("Z")};
	runTest(true, (expectedException != null), expectedException, -1);

	// compare via files
	if (expectedException == null)
	compareResults(1e-9);

	assert(checkedPrivacyConstraintsContains(privacyLevel));

	TestUtils.shutdownThreads(t1, t2);

	rtplatform = platformOld;
	DMLScript.USE_LOCAL_SPARK_CONFIG = sparkConfigOld;
	}
	}