wuchong commented on a change in pull request #9764: [FLINK-12939][docs-zh]
Translate "Apache Kafka Connector" page into Chinese
URL: https://github.com/apache/flink/pull/9764#discussion_r340037621
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File path: docs/dev/connectors/kafka.zh.md
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@@ -577,171 +474,101 @@ stream.addSink(myProducer);
val stream: DataStream[String] = ...
val myProducer = new FlinkKafkaProducer011[String](
- "localhost:9092", // broker list
- "my-topic", // target topic
- new SimpleStringSchema) // serialization schema
+ "localhost:9092", // broker 列表
+ "my-topic", // 目标 topic
+ new SimpleStringSchema) // 序列化 schema
-// versions 0.10+ allow attaching the records' event timestamp when writing
them to Kafka;
-// this method is not available for earlier Kafka versions
+// 0.10+ 版本的 Kafka 允许在将记录写入 Kafka 时附加记录的事件时间戳；
+// 此方法不适用于早期版本的 Kafka
myProducer.setWriteTimestampToKafka(true)
stream.addSink(myProducer)
{% endhighlight %}
</div>
</div>
-The above examples demonstrate the basic usage of creating a Flink Kafka
Producer
-to write streams to a single Kafka target topic. For more advanced usages,
there
-are other constructor variants that allow providing the following:
-
- * *Providing custom properties*:
- The producer allows providing a custom properties configuration for the
internal `KafkaProducer`.
- Please refer to the [Apache Kafka
documentation](https://kafka.apache.org/documentation.html) for
- details on how to configure Kafka Producers.
- * *Custom partitioner*: To assign records to specific
- partitions, you can provide an implementation of a `FlinkKafkaPartitioner` to
the
- constructor. This partitioner will be called for each record in the stream
- to determine which exact partition of the target topic the record should be
sent to.
- Please see [Kafka Producer Partitioning
Scheme](#kafka-producer-partitioning-scheme) for more details.
- * *Advanced serialization schema*: Similar to the consumer,
- the producer also allows using an advanced serialization schema called
`KeyedSerializationSchema`,
- which allows serializing the key and value separately. It also allows to
override the target topic,
- so that one producer instance can send data to multiple topics.
-
-### Kafka Producer Partitioning Scheme
-
-By default, if a custom partitioner is not specified for the Flink Kafka
Producer, the producer will use
-a `FlinkFixedPartitioner` that maps each Flink Kafka Producer parallel subtask
to a single Kafka partition
-(i.e., all records received by a sink subtask will end up in the same Kafka
partition).
-
-A custom partitioner can be implemented by extending the
`FlinkKafkaPartitioner` class. All
-Kafka versions' constructors allow providing a custom partitioner when
instantiating the producer.
-Note that the partitioner implementation must be serializable, as they will be
transferred across Flink nodes.
-Also, keep in mind that any state in the partitioner will be lost on job
failures since the partitioner
-is not part of the producer's checkpointed state.
-
-It is also possible to completely avoid using and kind of partitioner, and
simply let Kafka partition
-the written records by their attached key (as determined for each record using
the provided serialization schema).
-To do this, provide a `null` custom partitioner when instantiating the
producer. It is important
-to provide `null` as the custom partitioner; as explained above, if a custom
partitioner is not specified
-the `FlinkFixedPartitioner` is used instead.
-
-### Kafka Producers and Fault Tolerance
+上面的例子演示了创建 Flink Kafka Producer 来将流消息写入单个 Kafka 目标 topic 的基本用法。
+对于更高级的用法，这还有其他构造函数变体允许提供以下内容：
+
+ * *提供自定义属性*：producer 允许为内部 `KafkaProducer` 提供自定义属性配置。有关如何配置 Kafka Producer
的详细信息，请参阅 [Apache Kafka 文档](https://kafka.apache.org/documentation.html)。
+ * *自定义分区器*：要将消息分配给特定的分区，可以向构造函数提供一个 `FlinkKafkaPartitioner`
的实现。这个分区器将被流中的每条记录调用，以确定消息应该发送到目标 topic 的哪个具体分区里。有关详细信息，请参阅 [Kafka Producer
分区方案](#kafka-producer-partitioning-scheme)。
Review comment:
```suggestion
* *自定义分区器*：要将消息分配给特定的分区，可以向构造函数提供一个 `FlinkKafkaPartitioner`
的实现。这个分区器将被流中的每条记录调用，以确定消息应该发送到目标 topic 的哪个具体分区里。有关详细信息，请参阅 [Kafka Producer
分区方案](#kafka-producer-分区方案)。
```
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