| /* |
| * 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; |
| } |
| } |