xintongsong commented on a change in pull request #9677: [FLINK-13979]
[docs-zh] Translate new streamfilesink docs to chinese
URL: https://github.com/apache/flink/pull/9677#discussion_r324544533
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File path: docs/dev/connectors/streamfile_sink.zh.md
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@@ -28,80 +28,69 @@ under the License.
这个连接器提供了一个 Sink 来将分区文件写入到支持 [Flink `FileSystem`]({{
site.baseurl}}/zh/ops/filesystems/index.html) 接口的文件系统中。
-In order to handle unbounded data streams, the streaming file sink writes
incoming data
-into buckets. The bucketing behaviour is fully configurable with a default
time-based
-bucketing where we start writing a new bucket every hour and thus get files
that correspond to
-records received during certain time intervals from the stream.
+为了处理无界的流数据，Streaming File Sink
会将数据写入到桶中。如何分桶是可以配置的，默认策略是基于时间的分桶，这种策略每个小时创建并写入一个新的桶，从而得到流数据在特定时间间隔内接收记录所对应的文件。
-The bucket directories themselves contain several part files with the actual
output data, with at least
-one for each subtask of the sink that has received data for the bucket.
Additional part files will be created according to the configurable
-rolling policy. The default policy rolls files based on size, a timeout that
specifies the maximum duration for which a file can be open, and a maximum
inactivity timeout after which the file is closed.
+对于每一个接收桶数据的 Sink Subtask ，在桶中至少会存在一个正在接收数据的部分文件（part file）。其余的部分文件（part
file）将根据滚动策略创建，滚动策略是可以配置的。默认的策略是根据文件大小和超时时间来滚动文件。超时时间指打开文件的最长持续时间，以及文件关闭后的最长非活动时间。
<div class="alert alert-info">
- <b>IMPORTANT:</b> Checkpointing needs to be enabled when using the
StreamingFileSink. Part files can only be finalized
- on successful checkpoints. If checkpointing is disabled part files will
forever stay in `in-progress` or `pending` state
- and cannot be safely read by downstream systems.
+ <b>重要:</b> 使用 Streaming File Sink 时需要启用 Checkpoint ，每次做 Checkpoint
时滚动文件。如果 Checkpoint 被禁用，部分文件（part file）将永远处于 'in-progress' 或 'pending'
状态，下游系统无法安全地读取。
Review comment:
- finalize指的应该是写入完成，而不是滚动
- StreamingFileSink是类名，不可以用空格拆开
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