AlanConfluent commented on code in PR #24224:
URL: https://github.com/apache/flink/pull/24224#discussion_r1484927246
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docs/content/docs/dev/table/functions/udfs.md:
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@@ -846,6 +847,119 @@ If you intend to implement or call functions in Python,
please refer to the [Pyt
{{< top >}}
+Asynchronous Scalar Functions
+----------------
+
+A user-defined asynchronous scalar function maps zero, one, or multiple scalar
values to a new scalar value, but does it asynchronously. Any data type listed
in the [data types section]({{< ref "docs/dev/table/types" >}}) can be used as
a parameter or return type of an evaluation method.
+
+In order to define an asynchronous scalar function, one has to extend the base
class `AsyncScalarFunction` in `org.apache.flink.table.functions` and implement
one or more evaluation methods named `eval(...)`. The first argument must be a
`CompletableFuture<...>` which is used to return the result, with subsequent
arguments being the parameters passed to the function.
+
+The following example shows how to do work on a thread pool in the background,
though any libraries exposing an async interface may be directly used to
complete the `CompletableFuture` from a callback. See the [Implementation
Guide](#implementation-guide) for more details.
Review Comment:
I took a bunch of the introduction from that section. I also adopted the
diagram as well.
I also added sections for each of those you mentioned and explained how it
works, including citing specific configs and how they are used.
It should make a lot of sense and be easy for new users to understand, I
think. If there are areas which require more detail, please tell me and I can
add more. I just didn't want to make it too verbose vs other UDF descriptions.
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