weibozhao commented on code in PR #83: URL: https://github.com/apache/flink-ml/pull/83#discussion_r884801285
########## flink-ml-lib/src/main/java/org/apache/flink/ml/classification/logisticregression/OnlineLogisticRegression.java: ########## @@ -0,0 +1,434 @@ +/* + * 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.classification.logisticregression; + +import org.apache.flink.api.common.functions.FilterFunction; +import org.apache.flink.api.common.functions.MapFunction; +import org.apache.flink.api.common.functions.ReduceFunction; +import org.apache.flink.api.common.state.ListState; +import org.apache.flink.api.common.state.ListStateDescriptor; +import org.apache.flink.api.common.typeinfo.TypeInformation; +import org.apache.flink.api.java.typeutils.ObjectArrayTypeInfo; +import org.apache.flink.iteration.DataStreamList; +import org.apache.flink.iteration.IterationBody; +import org.apache.flink.iteration.IterationBodyResult; +import org.apache.flink.iteration.Iterations; +import org.apache.flink.iteration.operator.OperatorStateUtils; +import org.apache.flink.ml.api.Estimator; +import org.apache.flink.ml.common.datastream.DataStreamUtils; +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.runtime.state.StateInitializationContext; +import org.apache.flink.streaming.api.datastream.DataStream; +import org.apache.flink.streaming.api.operators.AbstractStreamOperator; +import org.apache.flink.streaming.api.operators.OneInputStreamOperator; +import org.apache.flink.streaming.api.operators.TwoInputStreamOperator; +import org.apache.flink.streaming.runtime.streamrecord.StreamRecord; +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.collections.IteratorUtils; + +import java.io.IOException; +import java.util.Arrays; +import java.util.HashMap; +import java.util.List; +import java.util.Map; + +/** + * An Estimator which implements the FTRL-Proximal online learning algorithm proposed by H. Brendan + * McMahan et al. + * + * <p>See <a href="https://doi.org/10.1145/2487575.2488200";>H. Brendan McMahan et al., Ad click + * prediction: a view from the trenches.</a> + */ +public class OnlineLogisticRegression + implements Estimator<OnlineLogisticRegression, OnlineLogisticRegressionModel>, + OnlineLogisticRegressionParams<OnlineLogisticRegression> { + private final Map<Param<?>, Object> paramMap = new HashMap<>(); + private Table initModelDataTable; + + public OnlineLogisticRegression() { + ParamUtils.initializeMapWithDefaultValues(paramMap, this); + } + + @Override + @SuppressWarnings("unchecked") + public OnlineLogisticRegressionModel fit(Table... inputs) { + Preconditions.checkArgument(inputs.length == 1); + + StreamTableEnvironment tEnv = + (StreamTableEnvironment) ((TableImpl) inputs[0]).getTableEnvironment(); + DataStream<LogisticRegressionModelData> modelDataStream = + LogisticRegressionModelData.getModelDataStream(initModelDataTable); + + DataStream<Row> points = + tEnv.toDataStream(inputs[0]) + .map(new FeaturesExtractor(getFeaturesCol(), getLabelCol())); + + DataStream<DenseVector> initModelData = + modelDataStream.map( + (MapFunction<LogisticRegressionModelData, DenseVector>) + value -> value.coefficient); Review Comment: modelVersion has been write to state. If restarting happened, algorithm will read the model version from checkpoint. Just as your example, if restarting happened at record 301, the model version data (without model version) is read from checkpoint in CalculateLocalGradient() and the modelVersion (modelVersion=3) is read from checkpoint in the CreateLrModelData() before sink model out. -- 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
