[GitHub] [flink] WeiZhong94 commented on a change in pull request #13070: [FLINK-18831][docs][python] Improve the documentation about the operations in Python Table API

[GitBox <gi...@apache.org>]

WeiZhong94 commented on a change in pull request #13070:
URL: https://github.com/apache/flink/pull/13070#discussion_r466150697



##########
File path: docs/dev/table/tableApi.md
##########
@@ -1490,8 +1558,12 @@ result = left.join(right).where("a = d && rowtime1 >= rowtime2 - 1.second
         <p>Joins a table with the results of a table function. Each row of the left (outer) table is joined with all rows produced by the corresponding call of the table function. A row of the left (outer) table is dropped, if its table function call returns an empty result.
         </p>
 {% highlight python %}
-# register Java User-Defined Table Function
-table_env.register_java_function("split", "com.my.udf.MySplitUDTF")
+# register User-Defined Table Function
+@udtf(input_types=[DataTypes.BIGINT()],
+      result_types=[DataTypes.BIGINT(), DataTypes.BIGINT(), DataTypes.BIGINT()])
+def split(x):
+    return [Row(1, 2, 3)]

Review comment:
       yield Row(1, 2, 3) ?

##########
File path: docs/dev/table/tableApi.md
##########
@@ -464,6 +485,49 @@ orders = table_env.from_path("Orders")
 {% endhighlight %}
       </td>
   	</tr>
+  	<tr>
+      <td>
+            <strong>FromElements</strong><br>
+            <span class="label label-primary">Batch</span> <span class="label label-primary">Streaming</span>
+      </td>
+      <td>
+          <p>Similar to the VALUES clause in a SQL query. Produces an inline table out of the provided rows.</p>
+{% highlight python %}
+table = tEnv.from_elements([(1, 'ABC'), (2, 'ABCDE')])

Review comment:
       t_env?

##########
File path: docs/dev/table/tableApi.md
##########
@@ -101,25 +101,49 @@ val result = orders
 </div>
 <div data-lang="python" markdown="1">
 
-The Python Table API is enabled by `from pyflink.table import *`.
-
 The following example shows how a Python Table API program is constructed and how expressions are specified as strings.
 
 {% highlight python %}
 from pyflink.table import *
-from pyflink.dataset import *
 
 # environment configuration
-env = ExecutionEnvironment.get_execution_environment()
-t_env = TableEnvironment.create(env, TableConfig())
+t_env = BatchTableEnvironment.create(
+    environment_settings=EnvironmentSettings.new_instance().in_batch_mode().use_blink_planner().build())
 
 # register Orders table and Result table sink in table environment
-# ...
+source_data_path = "/path/to/source/directory/"
+result_data_path = "/path/to/result/directory/"
+source_ddl = """

Review comment:
       It would be better if we use the format strings:
   f"""
              create table Orders(
               a VARCHAR,
               b BIGINT,
               c BIGINT,
               rowtime TIMESTAMP(3),
               WATERMARK FOR rowtime AS rowtime - INTERVAL '1' SECOND
           ) with (
               'connector' = 'filesystem',
               'format' = 'csv',
               'path' = '{source_data_path}'
           )
    """

##########
File path: docs/dev/table/tableApi.md
##########
@@ -1490,8 +1558,12 @@ result = left.join(right).where("a = d && rowtime1 >= rowtime2 - 1.second
         <p>Joins a table with the results of a table function. Each row of the left (outer) table is joined with all rows produced by the corresponding call of the table function. A row of the left (outer) table is dropped, if its table function call returns an empty result.
         </p>
 {% highlight python %}
-# register Java User-Defined Table Function
-table_env.register_java_function("split", "com.my.udf.MySplitUDTF")
+# register User-Defined Table Function
+@udtf(input_types=[DataTypes.BIGINT()],

Review comment:
       input_types is unnecessary now.




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