xiaoHoly commented on a change in pull request #13801:
URL: https://github.com/apache/flink/pull/13801#discussion_r513155682
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File path: docs/dev/table/connectors/formats/avro-confluent.zh.md
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@@ -29,27 +29,27 @@ under the License.
* This will be replaced by the TOC
{:toc}
-The Avro Schema Registry (``avro-confluent``) format allows you to read
records that were serialized by the
``io.confluent.kafka.serializers.KafkaAvroSerializer`` and to write records
that can in turn be read by the
``io.confluent.kafka.serializers.KafkaAvroDeserializer``.
+Avro Schema Registry (``avro-confluent``) 格式能让你读取被
``io.confluent.kafka.serializers.KafkaAvroSerializer``序列化的记录并可以写入成
``io.confluent.kafka.serializers.KafkaAvroDeserializer``反序列化的记录。
-When reading (deserializing) a record with this format the Avro writer schema
is fetched from the configured Confluent Schema Registry based on the schema
version id encoded in the record while the reader schema is inferred from table
schema.
+当以这种格式读取（反序列化）记录时，将根据记录中编码的 schema 版本 id 从配置的 Confluent Schema Registry 中获取
Avro writer schema ，而从 table schema 中推断出 reader schema。
-When writing (serializing) a record with this format the Avro schema is
inferred from the table schema and used to retrieve a schema id to be encoded
with the data. The lookup is performed with in the configured Confluent Schema
Registry under the
[subject](https://docs.confluent.io/current/schema-registry/index.html#schemas-subjects-and-topics)
given in `avro-confluent.schema-registry.subject`.
+当以这种格式写入（序列化）记录时，Avro schema 是从 table schema 中推断出来的，并用于检索要与数据一起编码的 schema
id。检索是在 Confluent Schema Registry 配置中的 `avro-confluent.schema-registry.subject`
中指定的[subject](https://docs.confluent.io/current/schema-registry/index.html#schemas-subjects-and-topics)下执行的。
Review comment:
thanks,i will update my code with your comments
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