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Posted to issues@flink.apache.org by GitBox <gi...@apache.org> on 2022/07/21 03:46:35 UTC
[GitHub] [flink-ml] zhipeng93 commented on a diff in pull request #131: [FLINK-28563] Add Transformer for VectorSlicer
zhipeng93 commented on code in PR #131:
URL: https://github.com/apache/flink-ml/pull/131#discussion_r926208138
##########
flink-ml-lib/src/main/java/org/apache/flink/ml/feature/vectorslicer/VectorSlicer.java:
##########
@@ -0,0 +1,138 @@
+/*
+ * 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.vectorslicer;
+
+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.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 feature transformer that transforms a vector to a new one with a sub-array of the original
Review Comment:
nit: Can you update the java doc as "A Transformer that..." following the existing java docs?
##########
flink-ml-lib/src/main/java/org/apache/flink/ml/feature/vectorslicer/VectorSlicer.java:
##########
@@ -0,0 +1,138 @@
+/*
+ * 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.vectorslicer;
+
+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.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 feature transformer that transforms a vector to a new one with a sub-array of the original
+ * features. It is useful for extracting features from a given vector. If the indices acquired from
+ * setIndices() are not in order, the indices of the result vector will be sorted.
+ */
+public class VectorSlicer implements Transformer<VectorSlicer>, VectorSlicerParams<VectorSlicer> {
+ private final Map<Param<?>, Object> paramMap = new HashMap<>();
+
+ public VectorSlicer() {
+ 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 VectorSlice(getIndices(), getInputCol()), outputTypeInfo);
+ Table outputTable = tEnv.fromDataStream(output);
+ return new Table[] {outputTable};
+ }
+
+ /** Vector slice function. */
+ public static class VectorSlice implements MapFunction<Row, Row> {
+ private final Integer[] indices;
+ private final String inputCol;
+
+ public VectorSlice(Integer[] indices, String inputCol) {
+ this.indices = indices;
+ this.inputCol = inputCol;
+ }
+
+ @Override
+ public Row map(Row row) throws Exception {
+ Vector inputVec = row.getFieldAs(inputCol);
+ Vector outputVec;
+ Arrays.sort(indices);
+ if (inputVec instanceof DenseVector) {
+ double[] values = new double[indices.length];
+ for (int i = 0; i < indices.length; ++i) {
+ if (indices[i] >= inputVec.size()) {
+ throw new RuntimeException("Index is larger than vector size.");
+ }
+ values[i] = ((DenseVector) inputVec).values[indices[i]];
+ }
+ outputVec = new DenseVector(values);
+ } else {
+ int nnz = 0;
+ SparseVector vec = (SparseVector) inputVec;
+ int[] outputIndices = new int[indices.length];
+ double[] outputValues = new double[indices.length];
+ for (int i = 0; i < indices.length; i++) {
+ if (indices[i] >= inputVec.size()) {
+ throw new RuntimeException("Index is larger than vector size.");
Review Comment:
Same as above.
##########
flink-ml-lib/src/main/java/org/apache/flink/ml/feature/vectorslicer/VectorSlicer.java:
##########
@@ -0,0 +1,138 @@
+/*
+ * 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.vectorslicer;
+
+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.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 feature transformer that transforms a vector to a new one with a sub-array of the original
+ * features. It is useful for extracting features from a given vector. If the indices acquired from
+ * setIndices() are not in order, the indices of the result vector will be sorted.
+ */
+public class VectorSlicer implements Transformer<VectorSlicer>, VectorSlicerParams<VectorSlicer> {
+ private final Map<Param<?>, Object> paramMap = new HashMap<>();
+
+ public VectorSlicer() {
+ 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 VectorSlice(getIndices(), getInputCol()), outputTypeInfo);
+ Table outputTable = tEnv.fromDataStream(output);
+ return new Table[] {outputTable};
+ }
+
+ /** Vector slice function. */
+ public static class VectorSlice implements MapFunction<Row, Row> {
+ private final Integer[] indices;
+ private final String inputCol;
+
+ public VectorSlice(Integer[] indices, String inputCol) {
+ this.indices = indices;
+ this.inputCol = inputCol;
+ }
+
+ @Override
+ public Row map(Row row) throws Exception {
+ Vector inputVec = row.getFieldAs(inputCol);
+ Vector outputVec;
+ Arrays.sort(indices);
+ if (inputVec instanceof DenseVector) {
+ double[] values = new double[indices.length];
+ for (int i = 0; i < indices.length; ++i) {
+ if (indices[i] >= inputVec.size()) {
+ throw new RuntimeException("Index is larger than vector size.");
Review Comment:
How about we only check the size of the inputVector is greater than the last element in the `indices`?
Also how about throwing a `IllegalArguementException` instead of `RuntimeException` here? Since it is wrong because of the illegal `indices`.
##########
flink-ml-lib/src/test/java/org/apache/flink/ml/feature/VectorSlicerTest.java:
##########
@@ -0,0 +1,166 @@
+/*
+ * 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.vectorslicer.VectorSlicer;
+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;
+
+/** Tests VectorSlicer. */
+public class VectorSlicerTest extends AbstractTestBase {
+
+ private StreamTableEnvironment tEnv;
+ private Table inputDataTable;
+
+ private static final List<Row> INPUT_DATA =
+ Arrays.asList(
+ Row.of(
+ 0,
+ Vectors.dense(2.1, 3.1, 2.3, 3.4, 5.3, 5.1),
+ Vectors.sparse(5, new int[] {1, 3, 4}, new double[] {0.1, 0.2, 0.3})),
+ Row.of(
+ 1,
+ Vectors.dense(2.3, 4.1, 1.3, 2.4, 5.1, 4.1),
+ Vectors.sparse(5, new int[] {1, 2, 4}, new double[] {0.1, 0.2, 0.3})));
+
+ private static final DenseVector EXPECTED_OUTPUT_DATA_1 = Vectors.dense(2.1, 3.1, 2.3);
+ private static final DenseVector EXPECTED_OUTPUT_DATA_2 = Vectors.dense(2.3, 4.1, 1.3);
+
+ private static final SparseVector EXPECTED_OUTPUT_DATA_3 =
+ Vectors.sparse(3, new int[] {1}, new double[] {0.1});
+ private static final SparseVector EXPECTED_OUTPUT_DATA_4 =
+ Vectors.sparse(3, new int[] {1, 2}, new double[] {0.1, 0.2});
+
+ @Before
+ public void before() {
+ Configuration config = new Configuration();
+ config.set(ExecutionCheckpointingOptions.ENABLE_CHECKPOINTS_AFTER_TASKS_FINISH, true);
+ StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment(config);
+ env.setParallelism(4);
+ env.enableCheckpointing(100);
+ env.setRestartStrategy(RestartStrategies.noRestart());
+ tEnv = StreamTableEnvironment.create(env);
+ DataStream<Row> dataStream = env.fromCollection(INPUT_DATA);
+ inputDataTable = tEnv.fromDataStream(dataStream).as("id", "vec", "sparseVec");
+ }
+
+ private void verifyOutputResult(Table output, String outputCol, boolean isSparse)
+ throws Exception {
+ DataStream<Row> dataStream = tEnv.toDataStream(output);
+ List<Row> results = IteratorUtils.toList(dataStream.executeAndCollect());
+ assertEquals(2, results.size());
+ for (Row result : results) {
+ if (result.getField(0) == (Object) 0) {
+ if (isSparse) {
+ assertEquals(EXPECTED_OUTPUT_DATA_3, result.getField(outputCol));
+ } else {
+ assertEquals(EXPECTED_OUTPUT_DATA_1, result.getField(outputCol));
+ }
+ } else if (result.getField(0) == (Object) 1) {
+ if (isSparse) {
+ assertEquals(EXPECTED_OUTPUT_DATA_4, result.getField(outputCol));
+ } else {
+ assertEquals(EXPECTED_OUTPUT_DATA_2, result.getField(outputCol));
+ }
+ }
+ }
+ }
+
+ @Test
+ public void testParam() {
+ VectorSlicer vectorSlicer = new VectorSlicer();
+ assertEquals("output", vectorSlicer.getOutputCol());
Review Comment:
Let's check the parameters in the same order, i.e., "inputCol, outputCol, indices" for consistency.
##########
flink-ml-lib/src/main/java/org/apache/flink/ml/feature/vectorslicer/VectorSlicer.java:
##########
@@ -0,0 +1,138 @@
+/*
+ * 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.vectorslicer;
+
+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.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 feature transformer that transforms a vector to a new one with a sub-array of the original
+ * features. It is useful for extracting features from a given vector. If the indices acquired from
+ * setIndices() are not in order, the indices of the result vector will be sorted.
+ */
+public class VectorSlicer implements Transformer<VectorSlicer>, VectorSlicerParams<VectorSlicer> {
+ private final Map<Param<?>, Object> paramMap = new HashMap<>();
+
+ public VectorSlicer() {
+ 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 VectorSlice(getIndices(), getInputCol()), outputTypeInfo);
+ Table outputTable = tEnv.fromDataStream(output);
+ return new Table[] {outputTable};
+ }
+
+ /** Vector slice function. */
+ public static class VectorSlice implements MapFunction<Row, Row> {
+ private final Integer[] indices;
+ private final String inputCol;
+
+ public VectorSlice(Integer[] indices, String inputCol) {
+ this.indices = indices;
+ this.inputCol = inputCol;
+ }
+
+ @Override
+ public Row map(Row row) throws Exception {
+ Vector inputVec = row.getFieldAs(inputCol);
+ Vector outputVec;
+ Arrays.sort(indices);
Review Comment:
How about move `sort` to the constructor method for high efficiency?
##########
flink-ml-lib/src/main/java/org/apache/flink/ml/feature/vectorslicer/VectorSlicer.java:
##########
@@ -0,0 +1,138 @@
+/*
+ * 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.vectorslicer;
+
+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.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 feature transformer that transforms a vector to a new one with a sub-array of the original
+ * features. It is useful for extracting features from a given vector. If the indices acquired from
+ * setIndices() are not in order, the indices of the result vector will be sorted.
+ */
+public class VectorSlicer implements Transformer<VectorSlicer>, VectorSlicerParams<VectorSlicer> {
+ private final Map<Param<?>, Object> paramMap = new HashMap<>();
+
+ public VectorSlicer() {
+ 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 VectorSlice(getIndices(), getInputCol()), outputTypeInfo);
+ Table outputTable = tEnv.fromDataStream(output);
+ return new Table[] {outputTable};
+ }
+
+ /** Vector slice function. */
+ public static class VectorSlice implements MapFunction<Row, Row> {
Review Comment:
nit: This method could be private and moved to the end of this java class.
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