RocMarshal commented on a change in pull request #18718:
URL: https://github.com/apache/flink/pull/18718#discussion_r809666287
##########
File path: docs/content.zh/docs/connectors/datastream/filesystem.md
##########
@@ -1023,60 +1026,50 @@ val fileSink: FileSink[Integer] =
**重要** 如果启用了文件合并功能，文件可见的时间会被延长。
{{< /hint >}}
-### Important Considerations
+<a name="important-considerations"></a>
+
+### 重要提示
Review comment:
```
### 重要注意事项
```
？
##########
File path: docs/content.zh/docs/connectors/datastream/filesystem.md
##########
@@ -1023,60 +1026,50 @@ val fileSink: FileSink[Integer] =
**重要** 如果启用了文件合并功能，文件可见的时间会被延长。
{{< /hint >}}
-### Important Considerations
+<a name="important-considerations"></a>
+
+### 重要提示
+
+<a name="general"></a>
+
+#### 整体提示
+
+<span class="label label-danger">重要提示 1</span>：当使用的 Hadoop 版本 < 2.7 时，
+当每次 Checkpoint 时请使用 `OnCheckpointRollingPolicy` 滚动 Part 文件。原因是：如果 Part 文件 "穿越"
了 Checkpoint 的时间间隔，
+然后，从失败中恢复过来时，`FileSink` 可能会使用文件系统的 `truncate()` 方法丢弃处于 In-progress 状态文件中的未提交数据。
+这个方法在 Hadoop 2.7 版本之前是不支持的，Flink 将抛出异常。
-#### General
+<span class="label label-danger">重要提示 2</span>：鉴于 Flink 的 Sink 和 UDF
通常不会区分正常作业终止（*例如* 有限输入流）和 由于故障而终止，
+在 Job 正常终止时，最后一个 In-progress 状态文件不会转换为 "Finished" 状态。
-<span class="label label-danger">Important Note 1</span>: When using Hadoop <
2.7, please use
-the `OnCheckpointRollingPolicy` which rolls part files on every checkpoint.
The reason is that if part files "traverse"
-the checkpoint interval, then, upon recovery from a failure the `FileSink` may
use the `truncate()` method of the
-filesystem to discard uncommitted data from the in-progress file. This method
is not supported by pre-2.7 Hadoop versions
-and Flink will throw an exception.
+<span class="label label-danger">重要提示 3</span>：Flink 和 `FileSink` 永远不会覆盖已提交数据。
+鉴于此，假定一个 In-progress 状态文件被后续成功的 Checkpoint 提交了，当尝试从这个旧的 Checkpoint / Savepoint
进行恢复时，`FileSink` 将拒绝继续执行并将抛出异常，因为程序无法找到 In-progress 状态的文件。
-<span class="label label-danger">Important Note 2</span>: Given that Flink
sinks and UDFs in general do not differentiate between
-normal job termination (*e.g.* finite input stream) and termination due to
failure, upon normal termination of a job, the last
-in-progress files will not be transitioned to the "finished" state.
+<span class="label label-danger">重要提示 4</span>：目前，`FileSink` 仅支持以下3种文件系统：HDFS、
S3 和 Local。如果在运行时使用了不支持的文件系统，Flink 将抛出异常。
-<span class="label label-danger">Important Note 3</span>: Flink and the
`FileSink` never overwrites committed data.
-Given this, when trying to restore from an old checkpoint/savepoint which
assumes an in-progress file which was committed
-by subsequent successful checkpoints, the `FileSink` will refuse to resume and
will throw an exception as it cannot locate the
-in-progress file.
+<a name="batch-specific"></a>
-<span class="label label-danger">Important Note 4</span>: Currently, the
`FileSink` only supports three filesystems:
-HDFS, S3, and Local. Flink will throw an exception when using an unsupported
filesystem at runtime.
+#### BATCH 提示
-#### BATCH-specific
+<span class="label label-danger">重要提示 1</span>：虽然 `Writer` 是以用户指定的 parallelism
执行的，然而 `Committer` 是以 parallelism = 1 执行的。
-<span class="label label-danger">Important Note 1</span>: Although the
`Writer` is executed with the user-specified
-parallelism, the `Committer` is executed with parallelism equal to 1.
+<span class="label label-danger">重要提示 2</span>：Pending
状态文件被提交并且所有输入数据被处理完后，才转换为 `Finished` 状态。
-<span class="label label-danger">Important Note 2</span>: Pending files are
committed, i.e. transition to `Finished`
-state, after the whole input has been processed.
+<span class="label label-danger">重要提示 3</span>：当系统处于高可用状态下，并且正当 `Committers`
进行提交时如果 `JobManager` 发生了故障，那么可能会有副本。这种情况将会在 Flink 的未来版本中进行修复。（可以参考
[FLIP-147](https://cwiki.apache.org/confluence/display/FLINK/FLIP-147%3A+Support+Checkpoints+After+Tasks+Finished)
） 。
-<span class="label label-danger">Important Note 3</span>: When
High-Availability is activated, if a `JobManager`
-failure happens while the `Committers` are committing, then we may have
duplicates. This is going to be fixed in
-future Flink versions
-(see progress in
[FLIP-147](https://cwiki.apache.org/confluence/display/FLINK/FLIP-147%3A+Support+Checkpoints+After+Tasks+Finished)).
+<a name="s3-specific"></a>
-#### S3-specific
+#### S3 提示
Review comment:
```suggestion
#### S3 注意事项
```
##########
File path: docs/content.zh/docs/connectors/datastream/filesystem.md
##########
@@ -1023,60 +1026,50 @@ val fileSink: FileSink[Integer] =
**重要** 如果启用了文件合并功能，文件可见的时间会被延长。
{{< /hint >}}
-### Important Considerations
+<a name="important-considerations"></a>
+
+### 重要提示
+
+<a name="general"></a>
+
+#### 整体提示
+
+<span class="label label-danger">重要提示 1</span>：当使用的 Hadoop 版本 < 2.7 时，
+当每次 Checkpoint 时请使用 `OnCheckpointRollingPolicy` 滚动 Part 文件。原因是：如果 Part 文件 "穿越"
了 Checkpoint 的时间间隔，
+然后，从失败中恢复过来时，`FileSink` 可能会使用文件系统的 `truncate()` 方法丢弃处于 In-progress 状态文件中的未提交数据。
+这个方法在 Hadoop 2.7 版本之前是不支持的，Flink 将抛出异常。
-#### General
+<span class="label label-danger">重要提示 2</span>：鉴于 Flink 的 Sink 和 UDF
通常不会区分正常作业终止（*例如* 有限输入流）和 由于故障而终止，
+在 Job 正常终止时，最后一个 In-progress 状态文件不会转换为 "Finished" 状态。
-<span class="label label-danger">Important Note 1</span>: When using Hadoop <
2.7, please use
-the `OnCheckpointRollingPolicy` which rolls part files on every checkpoint.
The reason is that if part files "traverse"
-the checkpoint interval, then, upon recovery from a failure the `FileSink` may
use the `truncate()` method of the
-filesystem to discard uncommitted data from the in-progress file. This method
is not supported by pre-2.7 Hadoop versions
-and Flink will throw an exception.
+<span class="label label-danger">重要提示 3</span>：Flink 和 `FileSink` 永远不会覆盖已提交数据。
+鉴于此，假定一个 In-progress 状态文件被后续成功的 Checkpoint 提交了，当尝试从这个旧的 Checkpoint / Savepoint
进行恢复时，`FileSink` 将拒绝继续执行并将抛出异常，因为程序无法找到 In-progress 状态的文件。
-<span class="label label-danger">Important Note 2</span>: Given that Flink
sinks and UDFs in general do not differentiate between
-normal job termination (*e.g.* finite input stream) and termination due to
failure, upon normal termination of a job, the last
-in-progress files will not be transitioned to the "finished" state.
+<span class="label label-danger">重要提示 4</span>：目前，`FileSink` 仅支持以下3种文件系统：HDFS、
S3 和 Local。如果在运行时使用了不支持的文件系统，Flink 将抛出异常。
-<span class="label label-danger">Important Note 3</span>: Flink and the
`FileSink` never overwrites committed data.
-Given this, when trying to restore from an old checkpoint/savepoint which
assumes an in-progress file which was committed
-by subsequent successful checkpoints, the `FileSink` will refuse to resume and
will throw an exception as it cannot locate the
-in-progress file.
+<a name="batch-specific"></a>
-<span class="label label-danger">Important Note 4</span>: Currently, the
`FileSink` only supports three filesystems:
-HDFS, S3, and Local. Flink will throw an exception when using an unsupported
filesystem at runtime.
+#### BATCH 提示
Review comment:
```suggestion
#### BATCH 注意事项
```
##########
File path: docs/content.zh/docs/connectors/datastream/filesystem.md
##########
@@ -1023,60 +1026,50 @@ val fileSink: FileSink[Integer] =
**重要** 如果启用了文件合并功能，文件可见的时间会被延长。
{{< /hint >}}
-### Important Considerations
+<a name="important-considerations"></a>
+
+### 重要提示
+
+<a name="general"></a>
+
+#### 整体提示
Review comment:
```
#### 整体提示
```
->
```
通用注意事项
```
？
Only a minor comment. Maybe you could do it better.
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