davidwrede commented on a change in pull request #13317:
URL: https://github.com/apache/beam/pull/13317#discussion_r523256644



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File path: website/www/site/content/en/documentation/programming-guide.md
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@@ -5431,4 +5431,282 @@ use case.
 
 {{< highlight py >}}
 {{< code_sample "sdks/python/apache_beam/examples/snippets/snippets.py" 
BundleFinalize >}}
-{{< /highlight >}}
\ No newline at end of file
+{{< /highlight >}}
+
+## 13. Multi-language pipelines {#mulit-language-pipelines}
+
+Beam allows you to combine transforms written in any supported SDK language 
(currently, Java and Python) and use them in one multi-language pipeline. This 
capability makes it easy to provide new functionality simultaneously in 
different Apache Beam SDKs through a single cross-language transform. For 
example, the Apache Kafka connector and SQL transform from the Java SDK can be 
used in Python streaming pipelines. 
+
+Pipelines that use transforms from more than one SDK-language are known as 
multi-language pipelines.

Review comment:
       Done.

##########
File path: website/www/site/content/en/documentation/programming-guide.md
##########
@@ -5431,4 +5431,282 @@ use case.
 
 {{< highlight py >}}
 {{< code_sample "sdks/python/apache_beam/examples/snippets/snippets.py" 
BundleFinalize >}}
-{{< /highlight >}}
\ No newline at end of file
+{{< /highlight >}}
+
+## 13. Multi-language pipelines {#mulit-language-pipelines}
+
+Beam allows you to combine transforms written in any supported SDK language 
(currently, Java and Python) and use them in one multi-language pipeline. This 
capability makes it easy to provide new functionality simultaneously in 
different Apache Beam SDKs through a single cross-language transform. For 
example, the Apache Kafka connector and SQL transform from the Java SDK can be 
used in Python streaming pipelines. 
+
+Pipelines that use transforms from more than one SDK-language are known as 
multi-language pipelines.
+
+### 13.1. Creating cross-language transforms {#create-x-lang-transforms}
+
+To make transforms written in one language available to pipelines written in 
another language, an expansion service for that transform is used to create and 
inject the appropriate language-specific pipeline fragments into your pipeline. 

Review comment:
       Done.




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