ektravel commented on a change in pull request #11975:
URL: https://github.com/apache/druid/pull/11975#discussion_r754571156



##########
File path: docs/development/extensions-core/avro.md
##########
@@ -22,47 +22,43 @@ title: "Apache Avro"
   ~ under the License.
   -->
 
-## Avro extension
+This Apache Druid extension enables Druid to ingest and parse the Apache Avro 
data format. The Avro extension enables the following ingestion input methods:
+- [Avro stream input format](../../ingestion/data-formats.md#avro-stream) for 
Kafka and Kinesis.
+- [Avro OCF input format](../../ingestion/data-formats.md#avro-ocf) for native 
batch ingestion.
+- [Avro Hadoop Parser](../../ingestion/data-formats.md#avro-hadoop-parser).
 
-This Apache Druid extension enables Druid to ingest and understand the Apache 
Avro data format. This extension provides 
-two Avro Parsers for stream ingestion and Hadoop batch ingestion. 
-See [Avro Hadoop Parser](../../ingestion/data-formats.md#avro-hadoop-parser) 
and [Avro Stream Parser](../../ingestion/data-formats.md#avro-stream-parser)
-for more details about how to use these in an ingestion spec.
+The [Avro Stream Parser](../../ingestion/data-formats.md#avro-stream-parser) 
is deprecated.
 
-Additionally, it provides an InputFormat for reading Avro OCF files when using
-[native batch indexing](../../ingestion/native-batch.md), see [Avro 
OCF](../../ingestion/data-formats.md#avro-ocf)
-for details on how to ingest OCF files.
+## Load the Avro extension
 
-Make sure to [include](../../development/extensions.md#loading-extensions) 
`druid-avro-extensions` in the extensions load list.
+To use the Avro extension, add the `druid-avro-extensions` to the list of 
loaded extensions. See [Loading 
extensions](../../development/extensions.md#loading-extensions).
 
-### Avro Types
+## Avro Types
 
-Druid supports most Avro types natively, there are however some exceptions 
which are detailed here.
+Druid supports most Avro types natively. This section describes some  
exceptions.
 
-#### Unions
+### Unions
 Druid has two modes for supporting `union` types.
 
-The default mode will treat unions as a single value regardless of the type it 
is populated with.
+The default mode treats unions as a single value regardless of the type of 
data populating the union.
 
-If you wish to operate on each different member of a union however you can set 
`extractUnionsByType` on the Avro parser in which case unions will be expanded 
into nested objects according to the following rules:
-* Primitive types and unnamed complex types are keyed their type name. i.e 
`int`, `string`
-* Complex named types are keyed by their names, this includes `record`, 
`fixed` and `enum`.
-* The Avro null type is elided as its value can only ever be null
+If you want to operate on individual members of a union, set 
`extractUnionsByType` on the Avro parser. This configuration expands union 
values into nested objects according to the following rules:
+- Primitive types and unnamed complex types are keyed their type name. For 
example: `int`, `string`
+- Complex named types are keyed by their names, this includes `record`, 
`fixed` and `enum`.
+- The Avro null type is elided as its value can only ever be null
 
-This is safe because an Avro union can only contain a single member of each 
unnamed type and duplicates of the same named type are not allowed.
-i.e only a single array is allowed, multiple records (or other named types) 
are allowed as long as each has a unique name.
+This is safe because an Avro union can only contain a single member of each 
unnamed type and duplicates of the same named type are not allowed. For 
example: only a single array is allowed, multiple records (or other named 
types) are allowed as long as each has a unique name.

Review comment:
       ```suggestion
   This is safe because an Avro union can only contain a single member of each 
unnamed type and duplicates of the same named type are not allowed. For 
example, only a single array is allowed, multiple records (or other named 
types) are allowed as long as each has a unique name.
   ```




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