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Posted to issues@flink.apache.org by GitBox <gi...@apache.org> on 2022/04/01 11:56:39 UTC
[GitHub] [flink-ml] weibozhao commented on a change in pull request #56: [FLINK-25616] Add Transformer for VectorAssembler
weibozhao commented on a change in pull request #56:
URL: https://github.com/apache/flink-ml/pull/56#discussion_r840513795
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File path: flink-ml-lib/src/main/java/org/apache/flink/ml/feature/vectorassembler/VectorAssembler.java
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@@ -0,0 +1,179 @@
+/*
+ * 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.vectorassembler;
+
+import org.apache.flink.api.common.functions.MapFunction;
+import org.apache.flink.api.common.typeinfo.TypeInformation;
+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.common.param.HasHandleInvalid;
+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.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.HashMap;
+import java.util.LinkedHashMap;
+import java.util.Map;
+
+/**
+ * Vector assembler is a transformer that combines a given list of columns into a single vector
+ * column. It will combine raw features and features generated by different feature transformers
+ * into a single feature vector. The input features of this transformer must be a vector feature or
+ * a numerical feature.
+ */
+public class VectorAssembler
+ implements Transformer<VectorAssembler>, VectorAssemblerParams<VectorAssembler> {
+ private final Map<Param<?>, Object> paramMap = new HashMap<>();
+ private static final double RATIO = 1.5;
+
+ public VectorAssembler() {
+ 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(), TypeInformation.of(Vector.class)),
+ ArrayUtils.addAll(inputTypeInfo.getFieldNames(), getOutputCol()));
+ DataStream<Row> output =
+ tEnv.toDataStream(inputs[0])
+ .map(new AssemblerFunc(getInputCols(), getHandleInvalid()), outputTypeInfo);
+ Table outputTable = tEnv.fromDataStream(output);
+ return new Table[] {outputTable};
+ }
+
+ private static class AssemblerFunc implements MapFunction<Row, Row> {
+ private final String[] inputCols;
+ private final String handleInvalid;
+
+ public AssemblerFunc(String[] inputCols, String handleInvalid) {
+ this.inputCols = inputCols;
+ this.handleInvalid = handleInvalid;
+ }
+
+ @Override
+ public Row map(Row value) {
+ Object[] objects = new Object[inputCols.length];
+ for (int i = 0; i < objects.length; ++i) {
+ objects[i] = value.getField(inputCols[i]);
+ }
+ return Row.join(value, Row.of(assemble(objects, handleInvalid)));
+ }
+ }
+
+ @Override
+ public void save(String path) throws IOException {
+ ReadWriteUtils.saveMetadata(this, path);
+ }
+
+ public static VectorAssembler load(StreamTableEnvironment env, String path) throws IOException {
+ return ReadWriteUtils.loadStageParam(path);
+ }
+
+ @Override
+ public Map<Param<?>, Object> getParamMap() {
+ return paramMap;
+ }
+
+ private static Vector assemble(Object[] objects, String handleInvalid) {
+ int offset = 0;
+ Map<Integer, Double> map = new LinkedHashMap<>(objects.length);
+ for (Object object : objects) {
+ try {
+ Preconditions.checkNotNull(object, "VectorAssembler Error: input data is null.");
+ if (object instanceof Number) {
+ map.put(offset++, ((Number) object).doubleValue());
+ } else if (object instanceof Vector) {
+ offset = appendVector((Vector) object, map, offset);
+ } else {
+ throw new UnsupportedOperationException(
+ "Vector assembler : input type has not been supported yet.");
+ }
+ } catch (Exception e) {
+ switch (handleInvalid) {
+ case HasHandleInvalid.ERROR_INVALID:
+ throw new RuntimeException("Vector assembler failed.", e);
+ case HasHandleInvalid.SKIP_INVALID:
+ return null;
Review comment:
I think "keep" is need here.
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