wuchong commented on a change in pull request #8918:
[FLINK-12944][docs]Translate Streaming File Sink page into Chinese
URL: https://github.com/apache/flink/pull/8918#discussion_r298822925
##########
File path: docs/dev/connectors/streamfile_sink.zh.md
##########
@@ -84,55 +77,41 @@ input.addSink(sink)
</div>
</div>
-This will create a streaming sink that creates hourly buckets and uses a
-default rolling policy. The default bucket assigner is
+上面的代码创建了一个按小时分桶、按默认策略滚动的 sink。默认分桶器是
[DateTimeBucketAssigner]({{ site.javadocs_baseurl
}}/api/java/org/apache/flink/streaming/api/functions/sink/filesystem/bucketassigners/DateTimeBucketAssigner.html)
-and the default rolling policy is
-[DefaultRollingPolicy]({{ site.javadocs_baseurl
}}/api/java/org/apache/flink/streaming/api/functions/sink/filesystem/rollingpolicies/DefaultRollingPolicy.html).
-You can specify a custom
+，默认滚动策略是
+[DefaultRollingPolicy]({{ site.javadocs_baseurl
}}/api/java/org/apache/flink/streaming/api/functions/sink/filesystem/rollingpolicies/DefaultRollingPolicy.html)。
+可以为 sink builder 自定义
[BucketAssigner]({{ site.javadocs_baseurl
}}/api/java/org/apache/flink/streaming/api/functions/sink/filesystem/BucketAssigner.html)
-and
-[RollingPolicy]({{ site.javadocs_baseurl
}}/api/java/org/apache/flink/streaming/api/functions/sink/filesystem/RollingPolicy.html)
-on the sink builder. Please check out the JavaDoc for
-[StreamingFileSink]({{ site.javadocs_baseurl
}}/api/java/org/apache/flink/streaming/api/functions/sink/filesystem/StreamingFileSink.html)
-for more configuration options and more documentation about the workings and
-interactions of bucket assigners and rolling policies.
+和
+[RollingPolicy]({{ site.javadocs_baseurl
}}/api/java/org/apache/flink/streaming/api/functions/sink/filesystem/RollingPolicy.html)。
+更多配置操作以及分桶器和滚动策略的工作机制和相互影响请参考：
+[StreamingFileSink]({{ site.javadocs_baseurl
}}/api/java/org/apache/flink/streaming/api/functions/sink/filesystem/StreamingFileSink.html)。
-#### Using Bulk-encoded Output Formats
+#### 使用批量编码输出格式
-In the above example we used an `Encoder` that can encode or serialize each
-record individually. The streaming file sink also supports bulk-encoded output
-formats such as [Apache Parquet](http://parquet.apache.org). To use these,
-instead of `StreamingFileSink.forRowFormat()` you would use
-`StreamingFileSink.forBulkFormat()` and specify a `BulkWriter.Factory`.
+上面的示例使用 `Encoder` 分别序列化每一个记录。除此之外，流式文件 sink 还支持批量编码的输出
+格式，比如 Apache Parquet](http://parquet.apache.org)。使用这种编码格式需要用
`StreamingFileSink.forBulkFormat()`
+来代替 `StreamingFileSink.forRowFormat()` ，然后指定一个 `BulkWriter.Factory`。
[ParquetAvroWriters]({{ site.javadocs_baseurl
}}/api/java/org/apache/flink/formats/parquet/avro/ParquetAvroWriters.html)
-has static methods for creating a `BulkWriter.Factory` for various types.
+中包含了为各种类型创建 `BulkWriter.Factory` 的静态方法。
<div class="alert alert-info">
- <b>IMPORTANT:</b> Bulk-encoding formats can only be combined with the
- `OnCheckpointRollingPolicy`, which rolls the in-progress part file on
- every checkpoint.
+ <b>IMPORTANT:</b> 批量编码格式只能和 `OnCheckpointRollingPolicy` 结合使用，每次做
checkpoint 时滚动文件。
</div>
-#### Important Considerations for S3
-
-<span class="label label-danger">Important Note 1</span>: For S3, the
`StreamingFileSink`
-supports only the [Hadoop-based](https://hadoop.apache.org/) FileSystem
implementation, not
-the implementation based on [Presto](https://prestodb.io/). In case your job
uses the
-`StreamingFileSink` to write to S3 but you want to use the Presto-based one
for checkpointing,
-it is advised to use explicitly *"s3a://"* (for Hadoop) as the scheme for the
target path of
-the sink and *"s3p://"* for checkpointing (for Presto). Using *"s3://"* for
both the sink
-and checkpointing may lead to unpredictable behavior, as both implementations
"listen" to that scheme.
-
-<span class="label label-danger">Important Note 2</span>: To guarantee
exactly-once semantics while
-being efficient, the `StreamingFileSink` uses the [Multi-part
Upload](https://docs.aws.amazon.com/AmazonS3/latest/dev/mpuoverview.html)
-feature of S3 (MPU from now on). This feature allows to upload files in
independent chunks (thus the "multi-part")
-which can be combined into the original file when all the parts of the MPU are
successfully uploaded.
-For inactive MPUs, S3 supports a bucket lifecycle rule that the user can use
to abort multipart uploads
-that don't complete within a specified number of days after being initiated.
This implies that if you set this rule
-aggressively and take a savepoint with some part-files being not fully
uploaded, their associated MPUs may time-out
-before the job is restarted. This will result in your job not being able to
restore from that savepoint as the
-pending part-files are no longer there and Flink will fail with an exception
as it tries to fetch them and fails.
+#### 关于S3的重要内容
+
+<span class="label label-danger">重要提示 1</span>: 对于 S3，`StreamingFileSink`
只支持基于 [Hadoop](https://hadoop.apache.org/)
+的文件系统实现，不支持基于 [Presto](https://prestodb.io/) 的实现。如果想使用 `StreamingFileSink` 向
S3 写入数据并且将
+checkpoint 放在基于 Presto 的文件系统，建议在 sink 路径中明确指定 *"s3a://"* 模式，在 checkpoint
路径中明确指定 *"s3p://"*
Review comment:
```suggestion
checkpoint 放在基于 Presto 的文件系统，建议明确指定 *"s3a://"* （为 Hadoop）作为sink的目标路径方案，并且为
checkpoint 路径明确指定 *"s3p://"* （为 Presto）
```
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