lindong28 commented on a change in pull request #70: URL: https://github.com/apache/flink-ml/pull/70#discussion_r835771045
########## File path: flink-ml-lib/src/main/java/org/apache/flink/ml/clustering/kmeans/OnlineKMeansModel.java ########## @@ -0,0 +1,182 @@ +/* + * 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.clustering.kmeans; + +import org.apache.flink.api.common.typeinfo.Types; +import org.apache.flink.api.java.typeutils.RowTypeInfo; +import org.apache.flink.configuration.Configuration; +import org.apache.flink.metrics.Gauge; +import org.apache.flink.ml.api.Model; +import org.apache.flink.ml.common.datastream.TableUtils; +import org.apache.flink.ml.common.distance.DistanceMeasure; +import org.apache.flink.ml.linalg.DenseVector; +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.streaming.api.environment.StreamExecutionEnvironment; +import org.apache.flink.streaming.api.functions.co.CoProcessFunction; +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.Collector; +import org.apache.flink.util.Preconditions; + +import org.apache.commons.lang3.ArrayUtils; + +import java.io.IOException; +import java.util.ArrayList; +import java.util.HashMap; +import java.util.List; +import java.util.Map; + +/** + * OnlineKMeansModel can be regarded as an advanced {@link KMeansModel} operator which can update + * model data in a streaming format, using the model data provided by {@link OnlineKMeans}. + */ +public class OnlineKMeansModel + implements Model<OnlineKMeansModel>, KMeansModelParams<OnlineKMeansModel> { + private final Map<Param<?>, Object> paramMap = new HashMap<>(); + private Table modelDataTable; + + public OnlineKMeansModel() { + ParamUtils.initializeMapWithDefaultValues(paramMap, this); + } + + @Override + public OnlineKMeansModel setModelData(Table... inputs) { + Preconditions.checkArgument(inputs.length == 1); + modelDataTable = inputs[0]; + return this; + } + + @Override + public Table[] getModelData() { + return new Table[] {modelDataTable}; + } + + @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(), Types.INT), + ArrayUtils.addAll(inputTypeInfo.getFieldNames(), getPredictionCol())); + + DataStream<Row> predictionResult = + KMeansModelData.getModelDataStream(modelDataTable) + .broadcast() + .connect(tEnv.toDataStream(inputs[0])) + .process( + new PredictLabelFunction( + getFeaturesCol(), + DistanceMeasure.getInstance(getDistanceMeasure())), + outputTypeInfo); + + return new Table[] {tEnv.fromDataStream(predictionResult)}; + } + + /** A utility function used for prediction. */ + private static class PredictLabelFunction extends CoProcessFunction<KMeansModelData, Row, Row> { + private final String featuresCol; + + private final DistanceMeasure distanceMeasure; + + private DenseVector[] centroids; + + // TODO: replace this with a complete solution of reading first model data from unbounded + // model data stream before processing the first predict data. + private final List<Row> bufferedPoints = new ArrayList<>(); Review comment: The long term solution is to `read first model data from unbounded model data stream before processing the first predict data`. If we can not achieve this goal, the OnlineKMeansModel won't be reliable for production anyway usage due to OOM. So it does not seem helpful to checkpoint the bufferedPoints here. -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: issues-unsubscr...@flink.apache.org For queries about this service, please contact Infrastructure at: us...@infra.apache.org
