zhipeng93 commented on a change in pull request #28:
URL: https://github.com/apache/flink-ml/pull/28#discussion_r767459284



##########
File path: 
flink-ml-core/src/main/java/org/apache/flink/ml/common/datastream/DataStreamUtils.java
##########
@@ -0,0 +1,125 @@
+/*
+ * 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.common.datastream;
+
+import org.apache.flink.api.common.functions.MapPartitionFunction;
+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.TypeExtractor;
+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.BoundedOneInput;
+import org.apache.flink.streaming.api.operators.OneInputStreamOperator;
+import org.apache.flink.streaming.api.operators.TimestampedCollector;
+import org.apache.flink.streaming.runtime.streamrecord.StreamRecord;
+
+/** Provides utility functions for {@link DataStream}. */
+public class DataStreamUtils {
+    /**
+     * Applies allReduceSum on the input data stream. The input data stream is 
supposed to contain
+     * one double array in each partition. The result data stream has the same 
parallelism as the
+     * input, where each partition contains one double array that sums all of 
the double arrays in
+     * the input data stream.
+     *
+     * <p>Note that we throw exception when one of the following two cases 
happen:
+     * <li>There exists one partition that contains more than one double array.
+     * <li>The length of the double array is not consistent among all 
partitions.
+     *
+     * @param input The input data stream.
+     * @return The result data stream.
+     */
+    public static DataStream<double[]> allReduceSum(DataStream<double[]> 
input) {
+        return AllReduceImpl.allReduceSum(input);
+    }
+
+    /**
+     * Applies a {@link MapPartitionFunction} on a bounded data stream.
+     *
+     * @param input The input data stream.
+     * @param func The user defined mapPartition function.
+     * @param <IN> The class type of the input element.
+     * @param <OUT> The class type of output element.
+     * @return The result data stream.
+     */
+    public static <IN, OUT> DataStream<OUT> mapPartition(
+            DataStream<IN> input, MapPartitionFunction<IN, OUT> func) {
+        TypeInformation<OUT> resultType =
+                TypeExtractor.getMapPartitionReturnTypes(func, 
input.getType(), null, true);
+        return input.transform("mapPartition", resultType, new 
MapPartitionOperator<>(func))
+                .setParallelism(input.getParallelism());
+    }
+
+    /**
+     * Applies a {@link MapPartitionFunction} on a bounded data stream.
+     *
+     * @param input The input data stream.
+     * @param func The user defined mapPartition function.
+     * @param outputType The type information of the output element.
+     * @param <IN> The class type of the input element.
+     * @param <OUT> The class type of output element.
+     * @return The result data stream.
+     */
+    public static <IN, OUT> DataStream<OUT> mapPartition(

Review comment:
       After some offline discussion, we agree to remove this method for now 
and add it back when needed.




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