zhipeng93 commented on code in PR #83:
URL: https://github.com/apache/flink-ml/pull/83#discussion_r854865460


##########
flink-ml-lib/src/main/java/org/apache/flink/ml/classification/logisticregression/OnlineLogisticRegressionModel.java:
##########
@@ -0,0 +1,225 @@
+/*
+ * 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.state.ListState;
+import org.apache.flink.api.common.state.ListStateDescriptor;
+import org.apache.flink.api.common.typeinfo.TypeInformation;
+import org.apache.flink.api.common.typeinfo.Types;
+import org.apache.flink.api.java.tuple.Tuple2;
+import org.apache.flink.api.java.typeutils.RowTypeInfo;
+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.linalg.BLAS;
+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.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.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.lang3.ArrayUtils;
+
+import java.io.IOException;
+import java.util.HashMap;
+import java.util.Map;
+
+/**
+ * A Model which classifies data using the model data computed by {@link 
OnlineLogisticRegression}.
+ */
+public class OnlineLogisticRegressionModel
+        implements Model<OnlineLogisticRegressionModel>,
+                
OnlineLogisticRegressionModelParams<OnlineLogisticRegressionModel> {
+    private final Map<Param<?>, Object> paramMap = new HashMap<>();
+    private Table modelDataTable;
+
+    public OnlineLogisticRegressionModel() {
+        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(),
+                                Types.DOUBLE,
+                                TypeInformation.of(DenseVector.class),
+                                Types.LONG),
+                        ArrayUtils.addAll(
+                                inputTypeInfo.getFieldNames(),
+                                getPredictionCol(),
+                                getRawPredictionCol(),
+                                getModelVersionCol()));

Review Comment:
   The behavior here is inconsistent with `OnlineKmeansModel`. We probably need 
to discuss about whether it is necessary to output the model version.



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