dianfu commented on a change in pull request #13663:
URL: https://github.com/apache/flink/pull/13663#discussion_r508158400
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File path: docs/dev/python/table-api-users-guide/udfs/vectorized_python_udfs.md
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@@ -62,3 +62,107 @@ my_table.select(add(my_table.bigint, my_table.bigint))
table_env.create_temporary_function("add", add)
table_env.sql_query("SELECT add(bigint, bigint) FROM MyTable")
{% endhighlight %}
+
+## Vectorized Aggregate Functions
+
+Vectorized Python aggregate functions takes one or more `pandas.Series` as the
inputs and return one scalar value as output.
+
+Vectorized Python aggregate function could be used in `GroupBy
Aggregation`(Batch), `GroupBy Window Aggregation`(Batch and Stream) and
+`Over Window Aggregation`(Batch and Stream bounded over window). For more
details on the usage of Aggregations, you can refer
+to [the relevant documentation]({% link dev/table/tableApi.md
%}?code_tab=python#aggregations).
+
+<span class="label label-info">Note</span> Pandas UDAF does not support
partial aggregation and all data for a group or window will be loaded into
memory.
Review comment:
```suggestion
<span class="label label-info">Note</span> Pandas UDAF does not support
partial aggregation. Besides, all the data for a group or window will be loaded
into memory during execution and so you must make sure that the data of a group
or window could fit into the memory.
```
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