jiangxin369 commented on code in PR #174:
URL: https://github.com/apache/flink-ml/pull/174#discussion_r1028792920


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flink-ml-lib/src/main/java/org/apache/flink/ml/feature/countvectorizer/CountVectorizer.java:
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@@ -0,0 +1,218 @@
+/*
+ * 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.countvectorizer;
+
+import org.apache.flink.api.common.functions.AggregateFunction;
+import org.apache.flink.api.common.functions.MapFunction;
+import org.apache.flink.api.java.tuple.Tuple2;
+import org.apache.flink.ml.api.Estimator;
+import org.apache.flink.ml.common.datastream.DataStreamUtils;
+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 java.io.IOException;
+import java.util.ArrayList;
+import java.util.Arrays;
+import java.util.HashMap;
+import java.util.List;
+import java.util.Map;
+import java.util.stream.Collectors;
+
+/**
+ * {@link CountVectorizer} aims to help convert a collection of text documents 
to vectors of token
+ * counts. When an a-priori dictionary is not available, {@link 
CountVectorizer} can be used as an
+ * estimator to extract the vocabulary, and generates a {@link 
CountVectorizerModel}. The model
+ * produces sparse representations for the documents over the vocabulary, 
which can then be passed
+ * to other algorithms like LDA.

Review Comment:
   * The JavaDoc often provides a description of the Estimator and starts with 
"An Estimator which", while the markdown starts with "CountVectorizer is an 
algorithm that ".
   * I'll remove the `@link`.



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