RocMarshal commented on a change in pull request #18655:
URL: https://github.com/apache/flink/pull/18655#discussion_r815783797
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File path: docs/content.zh/docs/connectors/table/filesystem.md
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@@ -190,209 +194,217 @@ CREATE TABLE MyUserTableWithFilepath (
)
```
+<a name="streaming-sink"></a>
+
## Streaming Sink
-The file system connector supports streaming writes, based on Flink's
[FileSystem]({{< ref "docs/connectors/datastream/filesystem" >}}),
-to write records to file. Row-encoded Formats are CSV and JSON. Bulk-encoded
Formats are Parquet, ORC and Avro.
+文件系统连接器支持流写入，是基于 Flink 的 [文件系统]({{< ref
"docs/connectors/datastream/filesystem" >}}) 写入文件的。CSV 和 JSON 使用的是 Row-encoded
Format。Parquet、ORC 和 Avro 使用的是 Bulk-encoded Format。
-You can write SQL directly, insert the stream data into the non-partitioned
table.
-If it is a partitioned table, you can configure partition related operations.
See [Partition Commit](filesystem.html#partition-commit) for details.
+可以直接编写 SQL，将流数据插入到非分区表。
+如果是分区表，可以配置分区操作相关的属性。请参考 [分区提交](#partition-commit) 了解更多详情。
Review comment:
```suggestion
如果是分区表，可以配置分区操作相关的属性。请参考[分区提交](#partition-commit)了解更多详情。
```
##########
File path: docs/content.zh/docs/connectors/table/filesystem.md
##########
@@ -190,209 +194,217 @@ CREATE TABLE MyUserTableWithFilepath (
)
```
+<a name="streaming-sink"></a>
+
## Streaming Sink
-The file system connector supports streaming writes, based on Flink's
[FileSystem]({{< ref "docs/connectors/datastream/filesystem" >}}),
-to write records to file. Row-encoded Formats are CSV and JSON. Bulk-encoded
Formats are Parquet, ORC and Avro.
+文件系统连接器支持流写入，是基于 Flink 的 [文件系统]({{< ref
"docs/connectors/datastream/filesystem" >}}) 写入文件的。CSV 和 JSON 使用的是 Row-encoded
Format。Parquet、ORC 和 Avro 使用的是 Bulk-encoded Format。
-You can write SQL directly, insert the stream data into the non-partitioned
table.
-If it is a partitioned table, you can configure partition related operations.
See [Partition Commit](filesystem.html#partition-commit) for details.
+可以直接编写 SQL，将流数据插入到非分区表。
+如果是分区表，可以配置分区操作相关的属性。请参考 [分区提交](#partition-commit) 了解更多详情。
-### Rolling Policy
+<a name="rolling-policy"></a>
-Data within the partition directories are split into part files. Each
partition will contain at least one part file for
-each subtask of the sink that has received data for that partition. The
in-progress part file will be closed and additional
-part file will be created according to the configurable rolling policy. The
policy rolls part files based on size,
-a timeout that specifies the maximum duration for which a file can be open.
+### 滚动策略
+
+分区目录下的数据被分割到 part 文件中。每个分区对应的 sink 的每个接收到的数据的 subtask 都至少会为该分区生成一个 part
文件。根据可配置的滚动策略，当前 in-progress part 文件将被关闭，生成新的 part 文件。该策略基于大小，和指定的文件可被打开的最大
timeout 时长，来滚动 part 文件。
Review comment:
```suggestion
分区目录下的数据被分割到 part 文件中。每个分区对应的 sink 的收到数据的 subtask 都至少会为该分区生成一个 part
文件。根据可配置的滚动策略，当前 in-progress part 文件将被关闭，生成新的 part 文件。该策略基于大小，和指定的文件可被打开的最大
timeout 时长，来滚动 part 文件。
```
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