davidradl commented on code in PR #26611:
URL: https://github.com/apache/flink/pull/26611#discussion_r2113912494
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docs/content/docs/dev/table/functions/udfs.md:
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@@ -1172,6 +1173,153 @@ If you intend to implement or call functions in Python,
please refer to the [Pyt
{{< top >}}
+Asynchronous Table Functions
+----------------
+
+Similar to `AsyncScalarFunction`, there also exists a `AsyncTableFunction` for
returning multiple row results rather than a single scalar value. Similarly,
this is most useful when interacting with external systems (for example when
enriching stream events with data stored in a database).
+
+Asynchronous interaction with an external system means that a single function
instance can handle many requests concurrently and receive the responses
concurrently. That way, the waiting time can be overlaid with sending other
requests and receiving responses. At the very least, the waiting time is
amortized over multiple requests. This leads in most cased to much higher
streaming throughput.
+
+#### Defining an AsyncTableFunction
+
+A user-defined asynchronous table function maps zero, one, or multiple scalar
values to zero, one, or multiple Rows, 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 table function, one has to extend the base
class `AsyncTableFunction` 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 number of outstanding calls to `eval` may be configured by
`table.exec.async-scalar.buffer-capacity`.
Review Comment:
maybe include a link to config parameter
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