zhipeng93 commented on code in PR #140: URL: https://github.com/apache/flink-ml/pull/140#discussion_r945496201
########## flink-ml-lib/src/test/java/org/apache/flink/ml/feature/InteractionTest.java: ########## @@ -0,0 +1,180 @@ +/* + * 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.flink.ml.feature; + +import org.apache.flink.api.common.restartstrategy.RestartStrategies; +import org.apache.flink.configuration.Configuration; +import org.apache.flink.ml.feature.interaction.Interaction; +import org.apache.flink.ml.linalg.DenseVector; +import org.apache.flink.ml.linalg.SparseVector; +import org.apache.flink.ml.linalg.Vectors; +import org.apache.flink.ml.util.TestUtils; +import org.apache.flink.streaming.api.datastream.DataStream; +import org.apache.flink.streaming.api.environment.ExecutionCheckpointingOptions; +import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment; +import org.apache.flink.table.api.Table; +import org.apache.flink.table.api.bridge.java.StreamTableEnvironment; +import org.apache.flink.test.util.AbstractTestBase; +import org.apache.flink.types.Row; + +import org.apache.commons.collections.IteratorUtils; +import org.junit.Before; +import org.junit.Test; + +import java.util.Arrays; +import java.util.List; + +import static org.junit.Assert.assertArrayEquals; +import static org.junit.Assert.assertEquals; +import static org.junit.Assert.assertNull; + +/** Tests {@link Interaction}. */ +public class InteractionTest extends AbstractTestBase { + + private StreamTableEnvironment tEnv; + private Table inputDataTable; + + private static final List<Row> INPUT_DATA = + Arrays.asList( + Row.of( + 1, + Vectors.dense(1, 2), + Vectors.dense(3, 4), + Vectors.sparse(17, new int[] {0, 3, 9}, new double[] {1.0, 2.0, 7.0})), + Row.of( + 2, + Vectors.dense(2, 8), + Vectors.dense(3, 4, 5), + Vectors.sparse(17, new int[] {0, 2, 14}, new double[] {5.0, 4.0, 1.0})), + Row.of(3, null, null, null)); + + private static final double[] EXPECTED_OUTPUT_DENSE_VEC_ARRAY_1 = Review Comment: nit: Could we simplify the test code here with the following code and also the `verifyOutputResult` method? ``` private static final List<DenseVector> EXPECTED_DENSE_OUTPUT = ... private static final List<DenseVector> EXPECTED_SPARSE_OUTPUT = ... ``` ########## flink-ml-lib/src/main/java/org/apache/flink/ml/feature/interaction/Interaction.java: ########## @@ -0,0 +1,183 @@ +/* + * 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.flink.ml.feature.interaction; + +import org.apache.flink.api.common.functions.MapFunction; +import org.apache.flink.api.java.typeutils.RowTypeInfo; +import org.apache.flink.ml.api.Transformer; +import org.apache.flink.ml.common.datastream.TableUtils; +import org.apache.flink.ml.linalg.DenseVector; +import org.apache.flink.ml.linalg.SparseVector; +import org.apache.flink.ml.linalg.Vector; +import org.apache.flink.ml.linalg.Vectors; +import org.apache.flink.ml.linalg.typeinfo.VectorTypeInfo; +import org.apache.flink.ml.param.Param; +import org.apache.flink.ml.util.ParamUtils; +import org.apache.flink.ml.util.ReadWriteUtils; +import org.apache.flink.streaming.api.datastream.DataStream; +import org.apache.flink.table.api.Table; +import org.apache.flink.table.api.bridge.java.StreamTableEnvironment; +import org.apache.flink.table.api.internal.TableImpl; +import org.apache.flink.types.Row; +import org.apache.flink.util.Preconditions; + +import org.apache.commons.lang3.ArrayUtils; + +import java.io.IOException; +import java.util.Arrays; +import java.util.HashMap; +import java.util.Map; + +/** + * A Transformer that takes vector or numerical columns, and generates a single vector column that + * contains the product of all combinations of one value from each input column. + * + * <p>For example, when the input feature values are Double(2) and Vector(3, 4), the output would be + * Vector(6, 8). When the input feature values are Vector(1, 2) and Vector(3, 4), the output would + * be Vector(3, 4, 6, 8). If you change the position of these two input Vectors, the output would be + * Vector(3, 6, 4, 8). + */ +public class Interaction implements Transformer<Interaction>, InteractionParams<Interaction> { + private final Map<Param<?>, Object> paramMap = new HashMap<>(); + + public Interaction() { + ParamUtils.initializeMapWithDefaultValues(paramMap, this); + } + + @Override + public Table[] transform(Table... inputs) { + Preconditions.checkArgument(inputs.length == 1); + StreamTableEnvironment tEnv = + (StreamTableEnvironment) ((TableImpl) inputs[0]).getTableEnvironment(); + RowTypeInfo inputTypeInfo = TableUtils.getRowTypeInfo(inputs[0].getResolvedSchema()); + RowTypeInfo outputTypeInfo = + new RowTypeInfo( + ArrayUtils.addAll(inputTypeInfo.getFieldTypes(), VectorTypeInfo.INSTANCE), + ArrayUtils.addAll(inputTypeInfo.getFieldNames(), getOutputCol())); + DataStream<Row> output = + tEnv.toDataStream(inputs[0]) + .map(new InteractionFunction(getInputCols()), outputTypeInfo); + Table outputTable = tEnv.fromDataStream(output); + return new Table[] {outputTable}; + } + + private static class InteractionFunction implements MapFunction<Row, Row> { + private final String[] inputCols; + private final int[] featureSize; + private final int[][] featureIndices; + private final double[][] featureValues; + + public InteractionFunction(String[] inputCols) { + this.inputCols = inputCols; + this.featureSize = new int[inputCols.length]; + this.featureIndices = new int[inputCols.length][]; + this.featureValues = new double[inputCols.length][]; + } + + @Override + public Row map(Row value) { + int nnz = 1; + boolean hasSparse = false; + for (int i = 0; i < inputCols.length; ++i) { + Object obj = value.getField(inputCols[i]); + if (obj == null) { + return Row.join(value, Row.of((Object) null)); + } + if (obj instanceof DenseVector) { + featureSize[i] = ((Vector) obj).size(); + if (featureIndices[i] == null || featureIndices[i].length != featureSize[i]) { + featureIndices[i] = new int[featureSize[i]]; + for (int j = 0; j < featureSize[i]; ++j) { + featureIndices[i][j] = j; + } + } + featureValues[i] = ((DenseVector) obj).values; + nnz *= featureSize[i]; + } else if (obj instanceof SparseVector) { + featureSize[i] = ((Vector) obj).size(); + featureIndices[i] = ((SparseVector) obj).indices; + featureValues[i] = ((SparseVector) obj).values; + nnz *= ((SparseVector) obj).values.length; + hasSparse = true; + } else { + featureSize[i] = 1; + if (featureIndices[i] == null) { Review Comment: nit: Is this line necessary here? -- This is an automated message from the Apache Git Service. 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