MemonaAmirAbdulHaq commented on code in PR #37543:
URL: https://github.com/apache/beam/pull/37543#discussion_r2818691829
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website/www/site/content/en/documentation/programming-guide.md:
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@@ -4164,14 +4164,31 @@ as schema fields may have different requirements or
restrictions from Go exporte
### 6.6. Using Schema Transforms {#using-schemas}
-A schema on a `PCollection` enables a rich variety of relational transforms.
The fact that each record is composed of
-named fields allows for simple and readable aggregations that reference fields
by name, similar to the aggregations in
-a SQL expression.
-
{{< paragraph class="language-go">}}
-Beam does not yet support Schema transforms natively in Go. However, it will
be implemented with the following behavior.
+In Go, schemas are inferred from struct types. You can use schema-aware
+<code>PCollection</code>s by defining structs and accessing their fields
+directly in transforms. The following example demonstrates extracting
+a nested field from a schema-aware collection.
{{< /paragraph >}}
+{{< highlight go >}}
+type ShippingAddress struct {
+ PostCode string `beam:"postCode"`
+ }
+type Purchase struct {
+ ShippingAddress ShippingAddress `beam:"shippingAddress"`
+ }
+purchases := beam.Create(s,
+ Purchase{
+ ShippingAddress: ShippingAddress{PostCode: "12345"},
+ },
+ )
+postCodes := beam.ParDo(s, func(p Purchase) string {
+ return p.ShippingAddress.PostCode
Review Comment:
Thanks for the feedback. I've restored the original schema description .
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