HuangXingBo commented on a change in pull request #13230:
URL: https://github.com/apache/flink/pull/13230#discussion_r480232415



##########
File path: docs/dev/python/user-guide/datastream/operations.md
##########
@@ -0,0 +1,87 @@
+---

Review comment:
       Rename the file to operators.md ?

##########
File path: docs/dev/python/user-guide/datastream/operations.md
##########
@@ -0,0 +1,87 @@
+---
+title: "Operators"
+nav-parent_id: python_datastream_api
+nav-pos: 20
+---
+<!--
+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.
+-->
+
+
+Operators transform one or more DataStreams into a new DataStream. Programs 
can combine multiple transformations into 
+sophisticated dataflow topologies.
+
+This section give a description of the basic transformations Python DataStream 
API provides, the effective physical 
+partitioning after applying those as well as insights into Flink's operator 
chaining.
+
+* This will be replaced by the TOC
+{:toc}
+
+# DataStream Transformations
+
+DataStream programs in Flink are regular programs that implement 
transformations on data streams (e.g., mapping, 
+filtering, reducing). Please see [operators]({% link 
dev/stream/operators/index.md %}
+?code_tab=python) for an overview of the available stream transformations in 
Python DataStream API.
+
+# Functions
+Most operators require a user-defined function. The following will describe 
different ways of how they can be specified.
+
+## Implementing Function Interfaces
+Function interfaces for different operations are provided in Python DataStream 
API. Users can implement a Function and 
+pass it to the corresponding operation. Take MapFunction for instance:
+<p>
+{% highlight python %}
+# Implement a MapFunction that return plus one value of input value.

Review comment:
       return -> returns

##########
File path: docs/dev/python/user-guide/datastream/operations.zh.md
##########
@@ -0,0 +1,77 @@
+---

Review comment:
       Rename the file to operators.zh.md ?

##########
File path: docs/dev/python/user-guide/datastream/operations.md
##########
@@ -0,0 +1,87 @@
+---
+title: "Operators"
+nav-parent_id: python_datastream_api
+nav-pos: 20
+---
+<!--
+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.
+-->
+
+
+Operators transform one or more DataStreams into a new DataStream. Programs 
can combine multiple transformations into 
+sophisticated dataflow topologies.
+
+This section give a description of the basic transformations Python DataStream 
API provides, the effective physical 
+partitioning after applying those as well as insights into Flink's operator 
chaining.
+
+* This will be replaced by the TOC
+{:toc}
+
+# DataStream Transformations
+
+DataStream programs in Flink are regular programs that implement 
transformations on data streams (e.g., mapping, 
+filtering, reducing). Please see [operators]({% link 
dev/stream/operators/index.md %}
+?code_tab=python) for an overview of the available stream transformations in 
Python DataStream API.
+
+# Functions
+Most operators require a user-defined function. The following will describe 
different ways of how they can be specified.
+
+## Implementing Function Interfaces
+Function interfaces for different operations are provided in Python DataStream 
API. Users can implement a Function and 
+pass it to the corresponding operation. Take MapFunction for instance:
+<p>
+{% highlight python %}
+# Implement a MapFunction that return plus one value of input value.
+class MyMapFunction(MapFunction):
+    
+    def map(value):
+        return value + 1
+        
+data_stream = env.from_collection([1, 2, 3, 4, 5],type_info=Types.INT())
+mapped_stream = data_stream.map(MyMapFunction(), output_type=Types.INT())
+{% endhighlight %}
+</p>
+<span class="label label-info">Note</span> In Python DataStream API, users are 
able to defined the output type information of the operation. If not 
+defined, the output type will be `Types.PICKLED_BYTE_ARRAY` that data will be 
in a form of byte array generated by 

Review comment:
       ```suggestion
   defined, the output type will be `Types.PICKLED_BYTE_ARRAY` so that data 
will be in a form of byte array generated by 
   ```

##########
File path: docs/dev/python/user-guide/datastream/operations.md
##########
@@ -0,0 +1,87 @@
+---
+title: "Operators"
+nav-parent_id: python_datastream_api
+nav-pos: 20
+---
+<!--
+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.
+-->
+
+
+Operators transform one or more DataStreams into a new DataStream. Programs 
can combine multiple transformations into 
+sophisticated dataflow topologies.
+
+This section give a description of the basic transformations Python DataStream 
API provides, the effective physical 
+partitioning after applying those as well as insights into Flink's operator 
chaining.
+
+* This will be replaced by the TOC
+{:toc}
+
+# DataStream Transformations
+
+DataStream programs in Flink are regular programs that implement 
transformations on data streams (e.g., mapping, 
+filtering, reducing). Please see [operators]({% link 
dev/stream/operators/index.md %}
+?code_tab=python) for an overview of the available stream transformations in 
Python DataStream API.
+
+# Functions
+Most operators require a user-defined function. The following will describe 
different ways of how they can be specified.
+
+## Implementing Function Interfaces
+Function interfaces for different operations are provided in Python DataStream 
API. Users can implement a Function and 
+pass it to the corresponding operation. Take MapFunction for instance:
+<p>
+{% highlight python %}
+# Implement a MapFunction that return plus one value of input value.
+class MyMapFunction(MapFunction):
+    
+    def map(value):
+        return value + 1
+        
+data_stream = env.from_collection([1, 2, 3, 4, 5],type_info=Types.INT())
+mapped_stream = data_stream.map(MyMapFunction(), output_type=Types.INT())
+{% endhighlight %}
+</p>
+<span class="label label-info">Note</span> In Python DataStream API, users are 
able to defined the output type information of the operation. If not 
+defined, the output type will be `Types.PICKLED_BYTE_ARRAY` that data will be 
in a form of byte array generated by 
+pickle seriallizer. For more detail, please refer to [DataTypes]({% link 
dev/python/user-guide/datastream/data_types.md

Review comment:
       ```suggestion
   pickle seriallizer. For more details on the `Pickle Serialization`
   , you can refer to [DataTypes]({% link 
dev/python/user-guide/datastream/data_types.md
   ```

##########
File path: docs/dev/python/user-guide/datastream/operations.md
##########
@@ -0,0 +1,87 @@
+---
+title: "Operators"
+nav-parent_id: python_datastream_api
+nav-pos: 20
+---
+<!--
+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.
+-->
+
+
+Operators transform one or more DataStreams into a new DataStream. Programs 
can combine multiple transformations into 
+sophisticated dataflow topologies.
+
+This section give a description of the basic transformations Python DataStream 
API provides, the effective physical 
+partitioning after applying those as well as insights into Flink's operator 
chaining.
+
+* This will be replaced by the TOC
+{:toc}
+
+# DataStream Transformations
+
+DataStream programs in Flink are regular programs that implement 
transformations on data streams (e.g., mapping, 
+filtering, reducing). Please see [operators]({% link 
dev/stream/operators/index.md %}
+?code_tab=python) for an overview of the available stream transformations in 
Python DataStream API.
+
+# Functions
+Most operators require a user-defined function. The following will describe 
different ways of how they can be specified.
+
+## Implementing Function Interfaces
+Function interfaces for different operations are provided in Python DataStream 
API. Users can implement a Function and 
+pass it to the corresponding operation. Take MapFunction for instance:
+<p>
+{% highlight python %}
+# Implement a MapFunction that return plus one value of input value.
+class MyMapFunction(MapFunction):
+    
+    def map(value):
+        return value + 1
+        
+data_stream = env.from_collection([1, 2, 3, 4, 5],type_info=Types.INT())
+mapped_stream = data_stream.map(MyMapFunction(), output_type=Types.INT())
+{% endhighlight %}
+</p>
+<span class="label label-info">Note</span> In Python DataStream API, users are 
able to defined the output type information of the operation. If not 
+defined, the output type will be `Types.PICKLED_BYTE_ARRAY` that data will be 
in a form of byte array generated by 
+pickle seriallizer. For more detail, please refer to [DataTypes]({% link 
dev/python/user-guide/datastream/data_types.md
+ %}).
+
+## Lambda Functions
+As shown in previous examples, all operations can also accept a lambda 
function for describing the operation:
+<p>
+{% highlight python %}
+data_stream = env.from_collection([1, 2, 3, 4, 5],type_info=Types.INT())
+mapped_stream = data_stream.map(lambda x: x + 1, output_type=Types.INT())
+{% endhighlight %}
+</p>
+<span class="label label-info">Note</span> Operations ConnectedStream.map() 
and ConnectedStream.flat_map() are

Review comment:
       ```suggestion
   <span class="label label-info">Note</span> The operations of map and 
flat_map in ConnectedStream only support accepting function interface
   ```

##########
File path: docs/dev/python/user-guide/datastream/operations.md
##########
@@ -0,0 +1,87 @@
+---
+title: "Operators"
+nav-parent_id: python_datastream_api
+nav-pos: 20
+---
+<!--
+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.
+-->
+
+
+Operators transform one or more DataStreams into a new DataStream. Programs 
can combine multiple transformations into 
+sophisticated dataflow topologies.
+
+This section give a description of the basic transformations Python DataStream 
API provides, the effective physical 
+partitioning after applying those as well as insights into Flink's operator 
chaining.
+
+* This will be replaced by the TOC
+{:toc}
+
+# DataStream Transformations
+
+DataStream programs in Flink are regular programs that implement 
transformations on data streams (e.g., mapping, 
+filtering, reducing). Please see [operators]({% link 
dev/stream/operators/index.md %}
+?code_tab=python) for an overview of the available stream transformations in 
Python DataStream API.
+
+# Functions
+Most operators require a user-defined function. The following will describe 
different ways of how they can be specified.
+
+## Implementing Function Interfaces
+Function interfaces for different operations are provided in Python DataStream 
API. Users can implement a Function and 
+pass it to the corresponding operation. Take MapFunction for instance:
+<p>
+{% highlight python %}
+# Implement a MapFunction that return plus one value of input value.
+class MyMapFunction(MapFunction):
+    
+    def map(value):
+        return value + 1
+        
+data_stream = env.from_collection([1, 2, 3, 4, 5],type_info=Types.INT())
+mapped_stream = data_stream.map(MyMapFunction(), output_type=Types.INT())
+{% endhighlight %}
+</p>
+<span class="label label-info">Note</span> In Python DataStream API, users are 
able to defined the output type information of the operation. If not 
+defined, the output type will be `Types.PICKLED_BYTE_ARRAY` that data will be 
in a form of byte array generated by 
+pickle seriallizer. For more detail, please refer to [DataTypes]({% link 
dev/python/user-guide/datastream/data_types.md
+ %}).

Review comment:
       ```suggestion
    %}#pickle-serialization).
   ```




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