[GitHub] [flink] klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh] Translate Savepoints page into Chinese
klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh]
Translate Savepoints page into Chinese
URL: https://github.com/apache/flink/pull/8300#discussion_r299767576
##
File path: docs/ops/state/savepoints.zh.md
##
@@ -25,32 +25,22 @@ under the License.
* toc
{:toc}
-## What is a Savepoint? How is a Savepoint different from a Checkpoint?
+## 什么是 Savepoint ？ Savepoint 与 Checkpoint 有什么不同？
-A Savepoint is a consistent image of the execution state of a streaming job,
created via Flink's [checkpointing mechanism]({{ site.baseurl
}}/internals/stream_checkpointing.html). You can use Savepoints to
stop-and-resume, fork,
-or update your Flink jobs. Savepoints consist of two parts: a directory with
(typically large) binary files on stable storage (e.g. HDFS, S3, ...) and a
(relatively small) meta data file. The files on stable storage represent the
net data of the job's execution state
-image. The meta data file of a Savepoint contains (primarily) pointers to all
files on stable storage that are part of the Savepoint, in form of absolute
paths.
+Savepoint 是依据 Flink [checkpointing 机制]({{ site.baseurl
}}/internals/stream_checkpointing.html)所创建的流作业执行状态的一致镜像。 你可以使用 Savepoint 进行
Flink 作业的停止与重启、fork或者更新。 Savepoint 由两部分组成：稳定存储（列入 HDFS，S3，...)
上包含二进制文件的目录（通常很大），和元数据文件（相对较小）。 稳定存储上的文件表示作业执行状态的数据镜像。 Savepoint
的元数据文件以（绝对路径）的形式包含（主要）指向作为 Savepoint 一部分的稳定存储上的所有文件的指针。
-Attention: In order to allow upgrades between programs and
Flink versions, it is important to check out the following section about assigning IDs to your operators.
+注意: 为了允许程序和 Flink 版本之间的升级，请务必查看以下有关分配算子 ID 的部分 。
+从概念上讲， Flink 的 Savepoint 与 Checkpoint 的不同之处类似于传统数据库中的备份与恢复日志之间的差异。 Checkpoint
的主要目的是为意外失败的作为提供恢复机制。 Checkpoint 的生命周期由 Flink 管理，即 Flink 创建，管理和删除 Checkpoint -
无需用户交互。 作为一种恢复和定期触发的方法，Checkpoint 实现有两个设计目标：i）轻量级创建和 ii）尽可能快地恢复。
可能会利用某些特定的属性来达到这个，例如， 工作代码在执行尝试之间不会改变。 在用户终止作业后，通常会删除 Checkpoint（除非明确配置为保留的
Checkpoint）。
-Conceptually, Flink's Savepoints are different from Checkpoints in a similar
way that backups are different from recovery logs in traditional database
systems. The primary purpose of Checkpoints is to provide a recovery mechanism
in case of
-unexpected job failures. A Checkpoint's lifecycle is managed by Flink, i.e. a
Checkpoint is created, owned, and released by Flink - without user interaction.
As a method of recovery and being periodically triggered, two main
-design goals for the Checkpoint implementation are i) being as lightweight to
create and ii) being as fast to restore from as possible. Optimizations towards
those goals can exploit certain properties, e.g. that the job code
-doesn't change between the execution attempts. Checkpoints are usually dropped
after the job was terminated by the user (except if explicitly configured as
retained Checkpoints).
+ 与此相反、Savepoint 由用户创建，拥有和删除。 他们的用例是计划的，手动备份和恢复。 例如，升级 Flink
版本，调整用户逻辑，改变并行度，以及进行红蓝部署等。 当然，Savepoint 必须在终止工作后继续存在。 从概念上讲，Savepoint
的生成，恢复成本可能更高一些，Savepoint 更多地关注可移植性和对前面提到的作业更改的支持。
Review comment:
personally, `用例是计划的` is a bit odd to me
`Savepoint 必须在终止工作后继续存在` --> `Savepoint 必须在作业停止后继续存在`
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[GitHub] [flink] klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh] Translate Savepoints page into Chinese
klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh]
Translate Savepoints page into Chinese
URL: https://github.com/apache/flink/pull/8300#discussion_r34599
##
File path: docs/ops/state/savepoints.zh.md
##
@@ -78,160 +68,162 @@ source-id | State of StatefulSource
mapper-id | State of StatefulMapper
{% endhighlight %}
-In the above example, the print sink is stateless and hence not part of the
savepoint state. By default, we try to map each entry of the savepoint back to
the new program.
+在上面的示例中，print sink 是无状态的，因此不是 Savepoint 状态的一部分。默认情况下，我们尝试将 Savepoint
的每个条目映射回新程序。
-## Operations
+## 算子
-You can use the [command line client]({{ site.baseurl
}}/ops/cli.html#savepoints) to *trigger savepoints*, *cancel a job with a
savepoint*, *resume from savepoints*, and *dispose savepoints*.
+你可以使用[命令行客户端]({{site.baseurl}}/zh/ops/cli.html#Savepoint)来*触发 Savepoint*，*触发
Savepoint 并取消作业*，*从 Savepoint*恢复，以及*删除 Savepoint*。
-With Flink >= 1.2.0 it is also possible to *resume from savepoints* using the
webui.
+从 Flink 1.2.0 开始，还可以使用 webui *从 Savepoint 恢复*。
-### Triggering Savepoints
+### 触发 Savepoint
-When triggering a savepoint, a new savepoint directory is created where the
data as well as the meta data will be stored. The location of this directory
can be controlled by [configuring a default target directory](#configuration)
or by specifying a custom target directory with the trigger commands (see the
[`:targetDirectory` argument](#trigger-a-savepoint)).
+当触发 Savepoint 时，将创建一个新的 Savepoint
目录，其中存储数据和元数据。可以通过[配置默认目标目录](#configuration)或使用触发器命令指定自定义目标目录(参见[`:targetDirectory
`参数](#trigger-a-savepoint)来控制该目录的位置。
-Attention: The target directory has to be a location
accessible by both the JobManager(s) and TaskManager(s) e.g. a location on a
distributed file-system.
+注意:目标目录必须是 JobManager(s) 和 TaskManager(s)
都可以访问的位置，例如分布式文件系统上的位置。
-For example with a `FsStateBackend` or `RocksDBStateBackend`:
+例如，使用 `FsStateBackend` 或 `RocksDBStateBackend` ：
{% highlight shell %}
-# Savepoint target directory
-/savepoints/
+# Savepoint 目标目录
+/Savepoint/
-# Savepoint directory
-/savepoints/savepoint-:shortjobid-:savepointid/
+# Savepoint 目录
+/Savepoint/savepoint-:shortjobid-:savepointid/
-# Savepoint file contains the checkpoint meta data
-/savepoints/savepoint-:shortjobid-:savepointid/_metadata
+# Savepoint 文件包含 Checkpoint元数据
+/Savepoint/savepoint-:shortjobid-:savepointid/_metadata
-# Savepoint state
-/savepoints/savepoint-:shortjobid-:savepointid/...
+# Savepoint 状态
+/Savepoint/savepoint-:shortjobid-:savepointid/...
{% endhighlight %}
- Note:
-Although it looks as if the savepoints may be moved, it is currently not
possible due to absolute paths in the _metadata file.
-Please follow https://issues.apache.org/jira/browse/FLINK-5778;>FLINK-5778 for
progress on lifting this restriction.
+ 注意:
+虽然看起来好像可以移动 Savepoint ，但由于 _metadata 中保存的是绝对路径，因此暂时不支持。
+请按照https://issues.apache.org/jira/browse/FLINK-5778;> FLINK-5778
了解取消此限制的进度。
-
-Note that if you use the `MemoryStateBackend`, metadata *and* savepoint state
will be stored in the `_metadata` file. Since it is self-contained, you may
move the file and restore from any location.
+请注意，如果使用 `MemoryStateBackend`，则元数据*和* Savepoint 状态将存储在`_metadata`文件中。
由于它是自包含的，你可以移动文件并从任何位置恢复。
- Attention: It is discouraged to move or delete the last
savepoint of a running job, because this might interfere with failure-recovery.
Savepoints have side-effects on exactly-once sinks, therefore
- to ensure exactly-once semantics, if there is no checkpoint after the last
savepoint, the savepoint will be used for recovery.
+ 注意: 不建议移动或删除正在运行作业的最后一个 Savepoint
，因为这可能会干扰故障恢复。因此，Savepoint 对精确一次的接收器有副作用，为了确保精确一次的语义，如果在最后一个 Savepoint 之后没有
Checkpoint ，那么将使用 Savepoint 进行恢复。
- Trigger a Savepoint
+
+ 触发 Savepoint
{% highlight shell %}
$ bin/flink savepoint :jobId [:targetDirectory]
{% endhighlight %}
-This will trigger a savepoint for the job with ID `:jobId`, and returns the
path of the created savepoint. You need this path to restore and dispose
savepoints.
+这将触发ID为`：jobId`的作业的Savepoint，并返回创建的 Savepoint 的路径。 你需要此路径来还原和部署 Savepoint 。
- Trigger a Savepoint with YARN
+ 使用 YARN 触发 Savepoint
{% highlight shell %}
$ bin/flink savepoint :jobId [:targetDirectory] -yid :yarnAppId
{% endhighlight %}
-This will trigger a savepoint for the job with ID `:jobId` and YARN
application ID `:yarnAppId`, and returns the path of the created savepoint.
+这将触发 ID 为`：jobId` 和 YARN 应用程序 ID `：yarnAppId`的作业的 Savepoint，并返回创建的 Savepoint
的路径。
- Cancel Job with Savepoint
+ 使用 Savepoint 取消作业
{% highlight shell %}
$ bin/flink cancel -s [:targetDirectory] :jobId
{% endhighlight %}
-This will atomically trigger a savepoint for the job with ID `:jobid` and
cancel the job. Furthermore, you can specify a target file system directory to
store the savepoint in. The directory needs to
[GitHub] [flink] klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh] Translate Savepoints page into Chinese
klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh]
Translate Savepoints page into Chinese
URL: https://github.com/apache/flink/pull/8300#discussion_r37951
##
File path: docs/ops/state/savepoints.zh.md
##
@@ -78,160 +68,162 @@ source-id | State of StatefulSource
mapper-id | State of StatefulMapper
{% endhighlight %}
-In the above example, the print sink is stateless and hence not part of the
savepoint state. By default, we try to map each entry of the savepoint back to
the new program.
+在上面的示例中，print sink 是无状态的，因此不是 Savepoint 状态的一部分。默认情况下，我们尝试将 Savepoint
的每个条目映射回新程序。
-## Operations
+## 算子
-You can use the [command line client]({{ site.baseurl
}}/ops/cli.html#savepoints) to *trigger savepoints*, *cancel a job with a
savepoint*, *resume from savepoints*, and *dispose savepoints*.
+你可以使用[命令行客户端]({{site.baseurl}}/zh/ops/cli.html#Savepoint)来*触发 Savepoint*，*触发
Savepoint 并取消作业*，*从 Savepoint*恢复，以及*删除 Savepoint*。
-With Flink >= 1.2.0 it is also possible to *resume from savepoints* using the
webui.
+从 Flink 1.2.0 开始，还可以使用 webui *从 Savepoint 恢复*。
-### Triggering Savepoints
+### 触发 Savepoint
-When triggering a savepoint, a new savepoint directory is created where the
data as well as the meta data will be stored. The location of this directory
can be controlled by [configuring a default target directory](#configuration)
or by specifying a custom target directory with the trigger commands (see the
[`:targetDirectory` argument](#trigger-a-savepoint)).
+当触发 Savepoint 时，将创建一个新的 Savepoint
目录，其中存储数据和元数据。可以通过[配置默认目标目录](#configuration)或使用触发器命令指定自定义目标目录(参见[`:targetDirectory
`参数](#trigger-a-savepoint)来控制该目录的位置。
-Attention: The target directory has to be a location
accessible by both the JobManager(s) and TaskManager(s) e.g. a location on a
distributed file-system.
+注意:目标目录必须是 JobManager(s) 和 TaskManager(s)
都可以访问的位置，例如分布式文件系统上的位置。
-For example with a `FsStateBackend` or `RocksDBStateBackend`:
+例如，使用 `FsStateBackend` 或 `RocksDBStateBackend` ：
{% highlight shell %}
-# Savepoint target directory
-/savepoints/
+# Savepoint 目标目录
+/Savepoint/
-# Savepoint directory
-/savepoints/savepoint-:shortjobid-:savepointid/
+# Savepoint 目录
+/Savepoint/savepoint-:shortjobid-:savepointid/
-# Savepoint file contains the checkpoint meta data
-/savepoints/savepoint-:shortjobid-:savepointid/_metadata
+# Savepoint 文件包含 Checkpoint元数据
+/Savepoint/savepoint-:shortjobid-:savepointid/_metadata
-# Savepoint state
-/savepoints/savepoint-:shortjobid-:savepointid/...
+# Savepoint 状态
+/Savepoint/savepoint-:shortjobid-:savepointid/...
{% endhighlight %}
- Note:
-Although it looks as if the savepoints may be moved, it is currently not
possible due to absolute paths in the _metadata file.
-Please follow https://issues.apache.org/jira/browse/FLINK-5778;>FLINK-5778 for
progress on lifting this restriction.
+ 注意:
+虽然看起来好像可以移动 Savepoint ，但由于 _metadata 中保存的是绝对路径，因此暂时不支持。
+请按照https://issues.apache.org/jira/browse/FLINK-5778;> FLINK-5778
了解取消此限制的进度。
-
-Note that if you use the `MemoryStateBackend`, metadata *and* savepoint state
will be stored in the `_metadata` file. Since it is self-contained, you may
move the file and restore from any location.
+请注意，如果使用 `MemoryStateBackend`，则元数据*和* Savepoint 状态将存储在`_metadata`文件中。
由于它是自包含的，你可以移动文件并从任何位置恢复。
- Attention: It is discouraged to move or delete the last
savepoint of a running job, because this might interfere with failure-recovery.
Savepoints have side-effects on exactly-once sinks, therefore
- to ensure exactly-once semantics, if there is no checkpoint after the last
savepoint, the savepoint will be used for recovery.
+ 注意: 不建议移动或删除正在运行作业的最后一个 Savepoint
，因为这可能会干扰故障恢复。因此，Savepoint 对精确一次的接收器有副作用，为了确保精确一次的语义，如果在最后一个 Savepoint 之后没有
Checkpoint ，那么将使用 Savepoint 进行恢复。
- Trigger a Savepoint
+
+ 触发 Savepoint
{% highlight shell %}
$ bin/flink savepoint :jobId [:targetDirectory]
{% endhighlight %}
-This will trigger a savepoint for the job with ID `:jobId`, and returns the
path of the created savepoint. You need this path to restore and dispose
savepoints.
+这将触发ID为`：jobId`的作业的Savepoint，并返回创建的 Savepoint 的路径。 你需要此路径来还原和部署 Savepoint 。
- Trigger a Savepoint with YARN
+ 使用 YARN 触发 Savepoint
{% highlight shell %}
$ bin/flink savepoint :jobId [:targetDirectory] -yid :yarnAppId
{% endhighlight %}
-This will trigger a savepoint for the job with ID `:jobId` and YARN
application ID `:yarnAppId`, and returns the path of the created savepoint.
+这将触发 ID 为`：jobId` 和 YARN 应用程序 ID `：yarnAppId`的作业的 Savepoint，并返回创建的 Savepoint
的路径。
- Cancel Job with Savepoint
+ 使用 Savepoint 取消作业
{% highlight shell %}
$ bin/flink cancel -s [:targetDirectory] :jobId
{% endhighlight %}
-This will atomically trigger a savepoint for the job with ID `:jobid` and
cancel the job. Furthermore, you can specify a target file system directory to
store the savepoint in. The directory needs to
[GitHub] [flink] klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh] Translate Savepoints page into Chinese
klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh]
Translate Savepoints page into Chinese
URL: https://github.com/apache/flink/pull/8300#discussion_r34992
##
File path: docs/ops/state/savepoints.zh.md
##
@@ -78,160 +68,162 @@ source-id | State of StatefulSource
mapper-id | State of StatefulMapper
{% endhighlight %}
-In the above example, the print sink is stateless and hence not part of the
savepoint state. By default, we try to map each entry of the savepoint back to
the new program.
+在上面的示例中，print sink 是无状态的，因此不是 Savepoint 状态的一部分。默认情况下，我们尝试将 Savepoint
的每个条目映射回新程序。
-## Operations
+## 算子
-You can use the [command line client]({{ site.baseurl
}}/ops/cli.html#savepoints) to *trigger savepoints*, *cancel a job with a
savepoint*, *resume from savepoints*, and *dispose savepoints*.
+你可以使用[命令行客户端]({{site.baseurl}}/zh/ops/cli.html#Savepoint)来*触发 Savepoint*，*触发
Savepoint 并取消作业*，*从 Savepoint*恢复，以及*删除 Savepoint*。
-With Flink >= 1.2.0 it is also possible to *resume from savepoints* using the
webui.
+从 Flink 1.2.0 开始，还可以使用 webui *从 Savepoint 恢复*。
-### Triggering Savepoints
+### 触发 Savepoint
-When triggering a savepoint, a new savepoint directory is created where the
data as well as the meta data will be stored. The location of this directory
can be controlled by [configuring a default target directory](#configuration)
or by specifying a custom target directory with the trigger commands (see the
[`:targetDirectory` argument](#trigger-a-savepoint)).
+当触发 Savepoint 时，将创建一个新的 Savepoint
目录，其中存储数据和元数据。可以通过[配置默认目标目录](#configuration)或使用触发器命令指定自定义目标目录(参见[`:targetDirectory
`参数](#trigger-a-savepoint)来控制该目录的位置。
-Attention: The target directory has to be a location
accessible by both the JobManager(s) and TaskManager(s) e.g. a location on a
distributed file-system.
+注意:目标目录必须是 JobManager(s) 和 TaskManager(s)
都可以访问的位置，例如分布式文件系统上的位置。
-For example with a `FsStateBackend` or `RocksDBStateBackend`:
+例如，使用 `FsStateBackend` 或 `RocksDBStateBackend` ：
{% highlight shell %}
-# Savepoint target directory
-/savepoints/
+# Savepoint 目标目录
+/Savepoint/
-# Savepoint directory
-/savepoints/savepoint-:shortjobid-:savepointid/
+# Savepoint 目录
+/Savepoint/savepoint-:shortjobid-:savepointid/
-# Savepoint file contains the checkpoint meta data
-/savepoints/savepoint-:shortjobid-:savepointid/_metadata
+# Savepoint 文件包含 Checkpoint元数据
+/Savepoint/savepoint-:shortjobid-:savepointid/_metadata
-# Savepoint state
-/savepoints/savepoint-:shortjobid-:savepointid/...
+# Savepoint 状态
+/Savepoint/savepoint-:shortjobid-:savepointid/...
{% endhighlight %}
- Note:
-Although it looks as if the savepoints may be moved, it is currently not
possible due to absolute paths in the _metadata file.
-Please follow https://issues.apache.org/jira/browse/FLINK-5778;>FLINK-5778 for
progress on lifting this restriction.
+ 注意:
+虽然看起来好像可以移动 Savepoint ，但由于 _metadata 中保存的是绝对路径，因此暂时不支持。
+请按照https://issues.apache.org/jira/browse/FLINK-5778;> FLINK-5778
了解取消此限制的进度。
-
-Note that if you use the `MemoryStateBackend`, metadata *and* savepoint state
will be stored in the `_metadata` file. Since it is self-contained, you may
move the file and restore from any location.
+请注意，如果使用 `MemoryStateBackend`，则元数据*和* Savepoint 状态将存储在`_metadata`文件中。
由于它是自包含的，你可以移动文件并从任何位置恢复。
- Attention: It is discouraged to move or delete the last
savepoint of a running job, because this might interfere with failure-recovery.
Savepoints have side-effects on exactly-once sinks, therefore
- to ensure exactly-once semantics, if there is no checkpoint after the last
savepoint, the savepoint will be used for recovery.
+ 注意: 不建议移动或删除正在运行作业的最后一个 Savepoint
，因为这可能会干扰故障恢复。因此，Savepoint 对精确一次的接收器有副作用，为了确保精确一次的语义，如果在最后一个 Savepoint 之后没有
Checkpoint ，那么将使用 Savepoint 进行恢复。
- Trigger a Savepoint
+
+ 触发 Savepoint
{% highlight shell %}
$ bin/flink savepoint :jobId [:targetDirectory]
{% endhighlight %}
-This will trigger a savepoint for the job with ID `:jobId`, and returns the
path of the created savepoint. You need this path to restore and dispose
savepoints.
+这将触发ID为`：jobId`的作业的Savepoint，并返回创建的 Savepoint 的路径。 你需要此路径来还原和部署 Savepoint 。
- Trigger a Savepoint with YARN
+ 使用 YARN 触发 Savepoint
{% highlight shell %}
$ bin/flink savepoint :jobId [:targetDirectory] -yid :yarnAppId
{% endhighlight %}
-This will trigger a savepoint for the job with ID `:jobId` and YARN
application ID `:yarnAppId`, and returns the path of the created savepoint.
+这将触发 ID 为`：jobId` 和 YARN 应用程序 ID `：yarnAppId`的作业的 Savepoint，并返回创建的 Savepoint
的路径。
- Cancel Job with Savepoint
+ 使用 Savepoint 取消作业
{% highlight shell %}
$ bin/flink cancel -s [:targetDirectory] :jobId
{% endhighlight %}
-This will atomically trigger a savepoint for the job with ID `:jobid` and
cancel the job. Furthermore, you can specify a target file system directory to
store the savepoint in. The directory needs to
[GitHub] [flink] klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh] Translate Savepoints page into Chinese
klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh]
Translate Savepoints page into Chinese
URL: https://github.com/apache/flink/pull/8300#discussion_r299767060
##
File path: docs/ops/state/savepoints.zh.md
##
@@ -25,32 +25,22 @@ under the License.
* toc
{:toc}
-## What is a Savepoint? How is a Savepoint different from a Checkpoint?
+## 什么是 Savepoint ？ Savepoint 与 Checkpoint 有什么不同？
-A Savepoint is a consistent image of the execution state of a streaming job,
created via Flink's [checkpointing mechanism]({{ site.baseurl
}}/internals/stream_checkpointing.html). You can use Savepoints to
stop-and-resume, fork,
-or update your Flink jobs. Savepoints consist of two parts: a directory with
(typically large) binary files on stable storage (e.g. HDFS, S3, ...) and a
(relatively small) meta data file. The files on stable storage represent the
net data of the job's execution state
-image. The meta data file of a Savepoint contains (primarily) pointers to all
files on stable storage that are part of the Savepoint, in form of absolute
paths.
+Savepoint 是依据 Flink [checkpointing 机制]({{ site.baseurl
}}/internals/stream_checkpointing.html)所创建的流作业执行状态的一致镜像。 你可以使用 Savepoint 进行
Flink 作业的停止与重启、fork或者更新。 Savepoint 由两部分组成：稳定存储（列入 HDFS，S3，...)
上包含二进制文件的目录（通常很大），和元数据文件（相对较小）。 稳定存储上的文件表示作业执行状态的数据镜像。 Savepoint
的元数据文件以（绝对路径）的形式包含（主要）指向作为 Savepoint 一部分的稳定存储上的所有文件的指针。
Review comment:
```suggestion
Savepoint 是依据 Flink [checkpointing 机制]({{ site.baseurl
}}/zh/internals/stream_checkpointing.html)所创建的流作业执行状态的一致镜像。 你可以使用 Savepoint 进行
Flink 作业的停止与重启、fork 或者更新。 Savepoint 由两部分组成：稳定存储（列入 HDFS，S3，...)
上包含二进制文件的目录（通常很大），和元数据文件（相对较小）。 稳定存储上的文件表示作业执行状态的数据镜像。 Savepoint
的元数据文件以（绝对路径）的形式包含（主要）指向作为 Savepoint 一部分的稳定存储上的所有文件的指针。
```
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[GitHub] [flink] klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh] Translate Savepoints page into Chinese
klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh]
Translate Savepoints page into Chinese
URL: https://github.com/apache/flink/pull/8300#discussion_r34462
##
File path: docs/ops/state/savepoints.zh.md
##
@@ -78,160 +68,162 @@ source-id | State of StatefulSource
mapper-id | State of StatefulMapper
{% endhighlight %}
-In the above example, the print sink is stateless and hence not part of the
savepoint state. By default, we try to map each entry of the savepoint back to
the new program.
+在上面的示例中，print sink 是无状态的，因此不是 Savepoint 状态的一部分。默认情况下，我们尝试将 Savepoint
的每个条目映射回新程序。
-## Operations
+## 算子
-You can use the [command line client]({{ site.baseurl
}}/ops/cli.html#savepoints) to *trigger savepoints*, *cancel a job with a
savepoint*, *resume from savepoints*, and *dispose savepoints*.
+你可以使用[命令行客户端]({{site.baseurl}}/zh/ops/cli.html#Savepoint)来*触发 Savepoint*，*触发
Savepoint 并取消作业*，*从 Savepoint*恢复，以及*删除 Savepoint*。
-With Flink >= 1.2.0 it is also possible to *resume from savepoints* using the
webui.
+从 Flink 1.2.0 开始，还可以使用 webui *从 Savepoint 恢复*。
-### Triggering Savepoints
+### 触发 Savepoint
-When triggering a savepoint, a new savepoint directory is created where the
data as well as the meta data will be stored. The location of this directory
can be controlled by [configuring a default target directory](#configuration)
or by specifying a custom target directory with the trigger commands (see the
[`:targetDirectory` argument](#trigger-a-savepoint)).
+当触发 Savepoint 时，将创建一个新的 Savepoint
目录，其中存储数据和元数据。可以通过[配置默认目标目录](#configuration)或使用触发器命令指定自定义目标目录(参见[`:targetDirectory
`参数](#trigger-a-savepoint)来控制该目录的位置。
-Attention: The target directory has to be a location
accessible by both the JobManager(s) and TaskManager(s) e.g. a location on a
distributed file-system.
+注意:目标目录必须是 JobManager(s) 和 TaskManager(s)
都可以访问的位置，例如分布式文件系统上的位置。
-For example with a `FsStateBackend` or `RocksDBStateBackend`:
+例如，使用 `FsStateBackend` 或 `RocksDBStateBackend` ：
{% highlight shell %}
-# Savepoint target directory
-/savepoints/
+# Savepoint 目标目录
+/Savepoint/
-# Savepoint directory
-/savepoints/savepoint-:shortjobid-:savepointid/
+# Savepoint 目录
+/Savepoint/savepoint-:shortjobid-:savepointid/
-# Savepoint file contains the checkpoint meta data
-/savepoints/savepoint-:shortjobid-:savepointid/_metadata
+# Savepoint 文件包含 Checkpoint元数据
+/Savepoint/savepoint-:shortjobid-:savepointid/_metadata
-# Savepoint state
-/savepoints/savepoint-:shortjobid-:savepointid/...
+# Savepoint 状态
+/Savepoint/savepoint-:shortjobid-:savepointid/...
{% endhighlight %}
- Note:
-Although it looks as if the savepoints may be moved, it is currently not
possible due to absolute paths in the _metadata file.
-Please follow https://issues.apache.org/jira/browse/FLINK-5778;>FLINK-5778 for
progress on lifting this restriction.
+ 注意:
+虽然看起来好像可以移动 Savepoint ，但由于 _metadata 中保存的是绝对路径，因此暂时不支持。
+请按照https://issues.apache.org/jira/browse/FLINK-5778;> FLINK-5778
了解取消此限制的进度。
-
-Note that if you use the `MemoryStateBackend`, metadata *and* savepoint state
will be stored in the `_metadata` file. Since it is self-contained, you may
move the file and restore from any location.
+请注意，如果使用 `MemoryStateBackend`，则元数据*和* Savepoint 状态将存储在`_metadata`文件中。
由于它是自包含的，你可以移动文件并从任何位置恢复。
- Attention: It is discouraged to move or delete the last
savepoint of a running job, because this might interfere with failure-recovery.
Savepoints have side-effects on exactly-once sinks, therefore
- to ensure exactly-once semantics, if there is no checkpoint after the last
savepoint, the savepoint will be used for recovery.
+ 注意: 不建议移动或删除正在运行作业的最后一个 Savepoint
，因为这可能会干扰故障恢复。因此，Savepoint 对精确一次的接收器有副作用，为了确保精确一次的语义，如果在最后一个 Savepoint 之后没有
Checkpoint ，那么将使用 Savepoint 进行恢复。
- Trigger a Savepoint
+
+ 触发 Savepoint
{% highlight shell %}
$ bin/flink savepoint :jobId [:targetDirectory]
{% endhighlight %}
-This will trigger a savepoint for the job with ID `:jobId`, and returns the
path of the created savepoint. You need this path to restore and dispose
savepoints.
+这将触发ID为`：jobId`的作业的Savepoint，并返回创建的 Savepoint 的路径。 你需要此路径来还原和部署 Savepoint 。
- Trigger a Savepoint with YARN
+ 使用 YARN 触发 Savepoint
{% highlight shell %}
$ bin/flink savepoint :jobId [:targetDirectory] -yid :yarnAppId
{% endhighlight %}
-This will trigger a savepoint for the job with ID `:jobId` and YARN
application ID `:yarnAppId`, and returns the path of the created savepoint.
+这将触发 ID 为`：jobId` 和 YARN 应用程序 ID `：yarnAppId`的作业的 Savepoint，并返回创建的 Savepoint
的路径。
- Cancel Job with Savepoint
+ 使用 Savepoint 取消作业
{% highlight shell %}
$ bin/flink cancel -s [:targetDirectory] :jobId
{% endhighlight %}
-This will atomically trigger a savepoint for the job with ID `:jobid` and
cancel the job. Furthermore, you can specify a target file system directory to
store the savepoint in. The directory needs to
[GitHub] [flink] klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh] Translate Savepoints page into Chinese
klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh]
Translate Savepoints page into Chinese
URL: https://github.com/apache/flink/pull/8300#discussion_r37693
##
File path: docs/ops/state/savepoints.zh.md
##
@@ -78,160 +68,162 @@ source-id | State of StatefulSource
mapper-id | State of StatefulMapper
{% endhighlight %}
-In the above example, the print sink is stateless and hence not part of the
savepoint state. By default, we try to map each entry of the savepoint back to
the new program.
+在上面的示例中，print sink 是无状态的，因此不是 Savepoint 状态的一部分。默认情况下，我们尝试将 Savepoint
的每个条目映射回新程序。
-## Operations
+## 算子
-You can use the [command line client]({{ site.baseurl
}}/ops/cli.html#savepoints) to *trigger savepoints*, *cancel a job with a
savepoint*, *resume from savepoints*, and *dispose savepoints*.
+你可以使用[命令行客户端]({{site.baseurl}}/zh/ops/cli.html#Savepoint)来*触发 Savepoint*，*触发
Savepoint 并取消作业*，*从 Savepoint*恢复，以及*删除 Savepoint*。
-With Flink >= 1.2.0 it is also possible to *resume from savepoints* using the
webui.
+从 Flink 1.2.0 开始，还可以使用 webui *从 Savepoint 恢复*。
-### Triggering Savepoints
+### 触发 Savepoint
-When triggering a savepoint, a new savepoint directory is created where the
data as well as the meta data will be stored. The location of this directory
can be controlled by [configuring a default target directory](#configuration)
or by specifying a custom target directory with the trigger commands (see the
[`:targetDirectory` argument](#trigger-a-savepoint)).
+当触发 Savepoint 时，将创建一个新的 Savepoint
目录，其中存储数据和元数据。可以通过[配置默认目标目录](#configuration)或使用触发器命令指定自定义目标目录(参见[`:targetDirectory
`参数](#trigger-a-savepoint)来控制该目录的位置。
-Attention: The target directory has to be a location
accessible by both the JobManager(s) and TaskManager(s) e.g. a location on a
distributed file-system.
+注意:目标目录必须是 JobManager(s) 和 TaskManager(s)
都可以访问的位置，例如分布式文件系统上的位置。
-For example with a `FsStateBackend` or `RocksDBStateBackend`:
+例如，使用 `FsStateBackend` 或 `RocksDBStateBackend` ：
{% highlight shell %}
-# Savepoint target directory
-/savepoints/
+# Savepoint 目标目录
+/Savepoint/
-# Savepoint directory
-/savepoints/savepoint-:shortjobid-:savepointid/
+# Savepoint 目录
+/Savepoint/savepoint-:shortjobid-:savepointid/
-# Savepoint file contains the checkpoint meta data
-/savepoints/savepoint-:shortjobid-:savepointid/_metadata
+# Savepoint 文件包含 Checkpoint元数据
+/Savepoint/savepoint-:shortjobid-:savepointid/_metadata
-# Savepoint state
-/savepoints/savepoint-:shortjobid-:savepointid/...
+# Savepoint 状态
+/Savepoint/savepoint-:shortjobid-:savepointid/...
{% endhighlight %}
- Note:
-Although it looks as if the savepoints may be moved, it is currently not
possible due to absolute paths in the _metadata file.
-Please follow https://issues.apache.org/jira/browse/FLINK-5778;>FLINK-5778 for
progress on lifting this restriction.
+ 注意:
+虽然看起来好像可以移动 Savepoint ，但由于 _metadata 中保存的是绝对路径，因此暂时不支持。
+请按照https://issues.apache.org/jira/browse/FLINK-5778;> FLINK-5778
了解取消此限制的进度。
-
-Note that if you use the `MemoryStateBackend`, metadata *and* savepoint state
will be stored in the `_metadata` file. Since it is self-contained, you may
move the file and restore from any location.
+请注意，如果使用 `MemoryStateBackend`，则元数据*和* Savepoint 状态将存储在`_metadata`文件中。
由于它是自包含的，你可以移动文件并从任何位置恢复。
- Attention: It is discouraged to move or delete the last
savepoint of a running job, because this might interfere with failure-recovery.
Savepoints have side-effects on exactly-once sinks, therefore
- to ensure exactly-once semantics, if there is no checkpoint after the last
savepoint, the savepoint will be used for recovery.
+ 注意: 不建议移动或删除正在运行作业的最后一个 Savepoint
，因为这可能会干扰故障恢复。因此，Savepoint 对精确一次的接收器有副作用，为了确保精确一次的语义，如果在最后一个 Savepoint 之后没有
Checkpoint ，那么将使用 Savepoint 进行恢复。
- Trigger a Savepoint
+
+ 触发 Savepoint
{% highlight shell %}
$ bin/flink savepoint :jobId [:targetDirectory]
{% endhighlight %}
-This will trigger a savepoint for the job with ID `:jobId`, and returns the
path of the created savepoint. You need this path to restore and dispose
savepoints.
+这将触发ID为`：jobId`的作业的Savepoint，并返回创建的 Savepoint 的路径。 你需要此路径来还原和部署 Savepoint 。
- Trigger a Savepoint with YARN
+ 使用 YARN 触发 Savepoint
{% highlight shell %}
$ bin/flink savepoint :jobId [:targetDirectory] -yid :yarnAppId
{% endhighlight %}
-This will trigger a savepoint for the job with ID `:jobId` and YARN
application ID `:yarnAppId`, and returns the path of the created savepoint.
+这将触发 ID 为`：jobId` 和 YARN 应用程序 ID `：yarnAppId`的作业的 Savepoint，并返回创建的 Savepoint
的路径。
- Cancel Job with Savepoint
+ 使用 Savepoint 取消作业
{% highlight shell %}
$ bin/flink cancel -s [:targetDirectory] :jobId
{% endhighlight %}
-This will atomically trigger a savepoint for the job with ID `:jobid` and
cancel the job. Furthermore, you can specify a target file system directory to
store the savepoint in. The directory needs to
[GitHub] [flink] klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh] Translate Savepoints page into Chinese
klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh]
Translate Savepoints page into Chinese
URL: https://github.com/apache/flink/pull/8300#discussion_r36608
##
File path: docs/ops/state/savepoints.zh.md
##
@@ -78,160 +68,162 @@ source-id | State of StatefulSource
mapper-id | State of StatefulMapper
{% endhighlight %}
-In the above example, the print sink is stateless and hence not part of the
savepoint state. By default, we try to map each entry of the savepoint back to
the new program.
+在上面的示例中，print sink 是无状态的，因此不是 Savepoint 状态的一部分。默认情况下，我们尝试将 Savepoint
的每个条目映射回新程序。
-## Operations
+## 算子
-You can use the [command line client]({{ site.baseurl
}}/ops/cli.html#savepoints) to *trigger savepoints*, *cancel a job with a
savepoint*, *resume from savepoints*, and *dispose savepoints*.
+你可以使用[命令行客户端]({{site.baseurl}}/zh/ops/cli.html#Savepoint)来*触发 Savepoint*，*触发
Savepoint 并取消作业*，*从 Savepoint*恢复，以及*删除 Savepoint*。
-With Flink >= 1.2.0 it is also possible to *resume from savepoints* using the
webui.
+从 Flink 1.2.0 开始，还可以使用 webui *从 Savepoint 恢复*。
-### Triggering Savepoints
+### 触发 Savepoint
-When triggering a savepoint, a new savepoint directory is created where the
data as well as the meta data will be stored. The location of this directory
can be controlled by [configuring a default target directory](#configuration)
or by specifying a custom target directory with the trigger commands (see the
[`:targetDirectory` argument](#trigger-a-savepoint)).
+当触发 Savepoint 时，将创建一个新的 Savepoint
目录，其中存储数据和元数据。可以通过[配置默认目标目录](#configuration)或使用触发器命令指定自定义目标目录(参见[`:targetDirectory
`参数](#trigger-a-savepoint)来控制该目录的位置。
-Attention: The target directory has to be a location
accessible by both the JobManager(s) and TaskManager(s) e.g. a location on a
distributed file-system.
+注意:目标目录必须是 JobManager(s) 和 TaskManager(s)
都可以访问的位置，例如分布式文件系统上的位置。
-For example with a `FsStateBackend` or `RocksDBStateBackend`:
+例如，使用 `FsStateBackend` 或 `RocksDBStateBackend` ：
{% highlight shell %}
-# Savepoint target directory
-/savepoints/
+# Savepoint 目标目录
+/Savepoint/
-# Savepoint directory
-/savepoints/savepoint-:shortjobid-:savepointid/
+# Savepoint 目录
+/Savepoint/savepoint-:shortjobid-:savepointid/
-# Savepoint file contains the checkpoint meta data
-/savepoints/savepoint-:shortjobid-:savepointid/_metadata
+# Savepoint 文件包含 Checkpoint元数据
+/Savepoint/savepoint-:shortjobid-:savepointid/_metadata
-# Savepoint state
-/savepoints/savepoint-:shortjobid-:savepointid/...
+# Savepoint 状态
+/Savepoint/savepoint-:shortjobid-:savepointid/...
{% endhighlight %}
- Note:
-Although it looks as if the savepoints may be moved, it is currently not
possible due to absolute paths in the _metadata file.
-Please follow https://issues.apache.org/jira/browse/FLINK-5778;>FLINK-5778 for
progress on lifting this restriction.
+ 注意:
+虽然看起来好像可以移动 Savepoint ，但由于 _metadata 中保存的是绝对路径，因此暂时不支持。
+请按照https://issues.apache.org/jira/browse/FLINK-5778;> FLINK-5778
了解取消此限制的进度。
-
-Note that if you use the `MemoryStateBackend`, metadata *and* savepoint state
will be stored in the `_metadata` file. Since it is self-contained, you may
move the file and restore from any location.
+请注意，如果使用 `MemoryStateBackend`，则元数据*和* Savepoint 状态将存储在`_metadata`文件中。
由于它是自包含的，你可以移动文件并从任何位置恢复。
- Attention: It is discouraged to move or delete the last
savepoint of a running job, because this might interfere with failure-recovery.
Savepoints have side-effects on exactly-once sinks, therefore
- to ensure exactly-once semantics, if there is no checkpoint after the last
savepoint, the savepoint will be used for recovery.
+ 注意: 不建议移动或删除正在运行作业的最后一个 Savepoint
，因为这可能会干扰故障恢复。因此，Savepoint 对精确一次的接收器有副作用，为了确保精确一次的语义，如果在最后一个 Savepoint 之后没有
Checkpoint ，那么将使用 Savepoint 进行恢复。
- Trigger a Savepoint
+
+ 触发 Savepoint
{% highlight shell %}
$ bin/flink savepoint :jobId [:targetDirectory]
{% endhighlight %}
-This will trigger a savepoint for the job with ID `:jobId`, and returns the
path of the created savepoint. You need this path to restore and dispose
savepoints.
+这将触发ID为`：jobId`的作业的Savepoint，并返回创建的 Savepoint 的路径。 你需要此路径来还原和部署 Savepoint 。
- Trigger a Savepoint with YARN
+ 使用 YARN 触发 Savepoint
{% highlight shell %}
$ bin/flink savepoint :jobId [:targetDirectory] -yid :yarnAppId
{% endhighlight %}
-This will trigger a savepoint for the job with ID `:jobId` and YARN
application ID `:yarnAppId`, and returns the path of the created savepoint.
+这将触发 ID 为`：jobId` 和 YARN 应用程序 ID `：yarnAppId`的作业的 Savepoint，并返回创建的 Savepoint
的路径。
- Cancel Job with Savepoint
+ 使用 Savepoint 取消作业
{% highlight shell %}
$ bin/flink cancel -s [:targetDirectory] :jobId
{% endhighlight %}
-This will atomically trigger a savepoint for the job with ID `:jobid` and
cancel the job. Furthermore, you can specify a target file system directory to
store the savepoint in. The directory needs to
[GitHub] [flink] klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh] Translate Savepoints page into Chinese
klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh]
Translate Savepoints page into Chinese
URL: https://github.com/apache/flink/pull/8300#discussion_r299973803
##
File path: docs/ops/state/savepoints.zh.md
##
@@ -78,160 +68,162 @@ source-id | State of StatefulSource
mapper-id | State of StatefulMapper
{% endhighlight %}
-In the above example, the print sink is stateless and hence not part of the
savepoint state. By default, we try to map each entry of the savepoint back to
the new program.
+在上面的示例中，print sink 是无状态的，因此不是 Savepoint 状态的一部分。默认情况下，我们尝试将 Savepoint
的每个条目映射回新程序。
-## Operations
+## 算子
-You can use the [command line client]({{ site.baseurl
}}/ops/cli.html#savepoints) to *trigger savepoints*, *cancel a job with a
savepoint*, *resume from savepoints*, and *dispose savepoints*.
+你可以使用[命令行客户端]({{site.baseurl}}/zh/ops/cli.html#Savepoint)来*触发 Savepoint*，*触发
Savepoint 并取消作业*，*从 Savepoint*恢复，以及*删除 Savepoint*。
-With Flink >= 1.2.0 it is also possible to *resume from savepoints* using the
webui.
+从 Flink 1.2.0 开始，还可以使用 webui *从 Savepoint 恢复*。
-### Triggering Savepoints
+### 触发 Savepoint
-When triggering a savepoint, a new savepoint directory is created where the
data as well as the meta data will be stored. The location of this directory
can be controlled by [configuring a default target directory](#configuration)
or by specifying a custom target directory with the trigger commands (see the
[`:targetDirectory` argument](#trigger-a-savepoint)).
+当触发 Savepoint 时，将创建一个新的 Savepoint
目录，其中存储数据和元数据。可以通过[配置默认目标目录](#configuration)或使用触发器命令指定自定义目标目录(参见[`:targetDirectory
`参数](#trigger-a-savepoint)来控制该目录的位置。
-Attention: The target directory has to be a location
accessible by both the JobManager(s) and TaskManager(s) e.g. a location on a
distributed file-system.
+注意:目标目录必须是 JobManager(s) 和 TaskManager(s)
都可以访问的位置，例如分布式文件系统上的位置。
-For example with a `FsStateBackend` or `RocksDBStateBackend`:
+例如，使用 `FsStateBackend` 或 `RocksDBStateBackend` ：
{% highlight shell %}
-# Savepoint target directory
-/savepoints/
+# Savepoint 目标目录
+/Savepoint/
-# Savepoint directory
-/savepoints/savepoint-:shortjobid-:savepointid/
+# Savepoint 目录
+/Savepoint/savepoint-:shortjobid-:savepointid/
-# Savepoint file contains the checkpoint meta data
-/savepoints/savepoint-:shortjobid-:savepointid/_metadata
+# Savepoint 文件包含 Checkpoint元数据
+/Savepoint/savepoint-:shortjobid-:savepointid/_metadata
-# Savepoint state
-/savepoints/savepoint-:shortjobid-:savepointid/...
+# Savepoint 状态
+/Savepoint/savepoint-:shortjobid-:savepointid/...
{% endhighlight %}
- Note:
-Although it looks as if the savepoints may be moved, it is currently not
possible due to absolute paths in the _metadata file.
-Please follow https://issues.apache.org/jira/browse/FLINK-5778;>FLINK-5778 for
progress on lifting this restriction.
+ 注意:
+虽然看起来好像可以移动 Savepoint ，但由于 _metadata 中保存的是绝对路径，因此暂时不支持。
+请按照https://issues.apache.org/jira/browse/FLINK-5778;> FLINK-5778
了解取消此限制的进度。
-
-Note that if you use the `MemoryStateBackend`, metadata *and* savepoint state
will be stored in the `_metadata` file. Since it is self-contained, you may
move the file and restore from any location.
+请注意，如果使用 `MemoryStateBackend`，则元数据*和* Savepoint 状态将存储在`_metadata`文件中。
由于它是自包含的，你可以移动文件并从任何位置恢复。
- Attention: It is discouraged to move or delete the last
savepoint of a running job, because this might interfere with failure-recovery.
Savepoints have side-effects on exactly-once sinks, therefore
- to ensure exactly-once semantics, if there is no checkpoint after the last
savepoint, the savepoint will be used for recovery.
+ 注意: 不建议移动或删除正在运行作业的最后一个 Savepoint
，因为这可能会干扰故障恢复。因此，Savepoint 对精确一次的接收器有副作用，为了确保精确一次的语义，如果在最后一个 Savepoint 之后没有
Checkpoint ，那么将使用 Savepoint 进行恢复。
- Trigger a Savepoint
+
+ 触发 Savepoint
{% highlight shell %}
$ bin/flink savepoint :jobId [:targetDirectory]
{% endhighlight %}
-This will trigger a savepoint for the job with ID `:jobId`, and returns the
path of the created savepoint. You need this path to restore and dispose
savepoints.
+这将触发ID为`：jobId`的作业的Savepoint，并返回创建的 Savepoint 的路径。 你需要此路径来还原和部署 Savepoint 。
- Trigger a Savepoint with YARN
+ 使用 YARN 触发 Savepoint
{% highlight shell %}
$ bin/flink savepoint :jobId [:targetDirectory] -yid :yarnAppId
{% endhighlight %}
-This will trigger a savepoint for the job with ID `:jobId` and YARN
application ID `:yarnAppId`, and returns the path of the created savepoint.
+这将触发 ID 为`：jobId` 和 YARN 应用程序 ID `：yarnAppId`的作业的 Savepoint，并返回创建的 Savepoint
的路径。
- Cancel Job with Savepoint
+ 使用 Savepoint 取消作业
{% highlight shell %}
$ bin/flink cancel -s [:targetDirectory] :jobId
{% endhighlight %}
-This will atomically trigger a savepoint for the job with ID `:jobid` and
cancel the job. Furthermore, you can specify a target file system directory to
store the savepoint in. The directory needs to
[GitHub] [flink] klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh] Translate Savepoints page into Chinese
klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh]
Translate Savepoints page into Chinese
URL: https://github.com/apache/flink/pull/8300#discussion_r33231
##
File path: docs/ops/state/savepoints.zh.md
##
@@ -78,160 +68,162 @@ source-id | State of StatefulSource
mapper-id | State of StatefulMapper
{% endhighlight %}
-In the above example, the print sink is stateless and hence not part of the
savepoint state. By default, we try to map each entry of the savepoint back to
the new program.
+在上面的示例中，print sink 是无状态的，因此不是 Savepoint 状态的一部分。默认情况下，我们尝试将 Savepoint
的每个条目映射回新程序。
-## Operations
+## 算子
-You can use the [command line client]({{ site.baseurl
}}/ops/cli.html#savepoints) to *trigger savepoints*, *cancel a job with a
savepoint*, *resume from savepoints*, and *dispose savepoints*.
+你可以使用[命令行客户端]({{site.baseurl}}/zh/ops/cli.html#Savepoint)来*触发 Savepoint*，*触发
Savepoint 并取消作业*，*从 Savepoint*恢复，以及*删除 Savepoint*。
-With Flink >= 1.2.0 it is also possible to *resume from savepoints* using the
webui.
+从 Flink 1.2.0 开始，还可以使用 webui *从 Savepoint 恢复*。
-### Triggering Savepoints
+### 触发 Savepoint
-When triggering a savepoint, a new savepoint directory is created where the
data as well as the meta data will be stored. The location of this directory
can be controlled by [configuring a default target directory](#configuration)
or by specifying a custom target directory with the trigger commands (see the
[`:targetDirectory` argument](#trigger-a-savepoint)).
+当触发 Savepoint 时，将创建一个新的 Savepoint
目录，其中存储数据和元数据。可以通过[配置默认目标目录](#configuration)或使用触发器命令指定自定义目标目录(参见[`:targetDirectory
`参数](#trigger-a-savepoint)来控制该目录的位置。
-Attention: The target directory has to be a location
accessible by both the JobManager(s) and TaskManager(s) e.g. a location on a
distributed file-system.
+注意:目标目录必须是 JobManager(s) 和 TaskManager(s)
都可以访问的位置，例如分布式文件系统上的位置。
-For example with a `FsStateBackend` or `RocksDBStateBackend`:
+例如，使用 `FsStateBackend` 或 `RocksDBStateBackend` ：
{% highlight shell %}
-# Savepoint target directory
-/savepoints/
+# Savepoint 目标目录
+/Savepoint/
-# Savepoint directory
-/savepoints/savepoint-:shortjobid-:savepointid/
+# Savepoint 目录
+/Savepoint/savepoint-:shortjobid-:savepointid/
-# Savepoint file contains the checkpoint meta data
-/savepoints/savepoint-:shortjobid-:savepointid/_metadata
+# Savepoint 文件包含 Checkpoint元数据
+/Savepoint/savepoint-:shortjobid-:savepointid/_metadata
-# Savepoint state
-/savepoints/savepoint-:shortjobid-:savepointid/...
+# Savepoint 状态
+/Savepoint/savepoint-:shortjobid-:savepointid/...
{% endhighlight %}
- Note:
-Although it looks as if the savepoints may be moved, it is currently not
possible due to absolute paths in the _metadata file.
-Please follow https://issues.apache.org/jira/browse/FLINK-5778;>FLINK-5778 for
progress on lifting this restriction.
+ 注意:
+虽然看起来好像可以移动 Savepoint ，但由于 _metadata 中保存的是绝对路径，因此暂时不支持。
+请按照https://issues.apache.org/jira/browse/FLINK-5778;> FLINK-5778
了解取消此限制的进度。
-
-Note that if you use the `MemoryStateBackend`, metadata *and* savepoint state
will be stored in the `_metadata` file. Since it is self-contained, you may
move the file and restore from any location.
+请注意，如果使用 `MemoryStateBackend`，则元数据*和* Savepoint 状态将存储在`_metadata`文件中。
由于它是自包含的，你可以移动文件并从任何位置恢复。
- Attention: It is discouraged to move or delete the last
savepoint of a running job, because this might interfere with failure-recovery.
Savepoints have side-effects on exactly-once sinks, therefore
- to ensure exactly-once semantics, if there is no checkpoint after the last
savepoint, the savepoint will be used for recovery.
+ 注意: 不建议移动或删除正在运行作业的最后一个 Savepoint
，因为这可能会干扰故障恢复。因此，Savepoint 对精确一次的接收器有副作用，为了确保精确一次的语义，如果在最后一个 Savepoint 之后没有
Checkpoint ，那么将使用 Savepoint 进行恢复。
- Trigger a Savepoint
+
+ 触发 Savepoint
{% highlight shell %}
$ bin/flink savepoint :jobId [:targetDirectory]
{% endhighlight %}
-This will trigger a savepoint for the job with ID `:jobId`, and returns the
path of the created savepoint. You need this path to restore and dispose
savepoints.
+这将触发ID为`：jobId`的作业的Savepoint，并返回创建的 Savepoint 的路径。 你需要此路径来还原和部署 Savepoint 。
- Trigger a Savepoint with YARN
+ 使用 YARN 触发 Savepoint
{% highlight shell %}
$ bin/flink savepoint :jobId [:targetDirectory] -yid :yarnAppId
{% endhighlight %}
-This will trigger a savepoint for the job with ID `:jobId` and YARN
application ID `:yarnAppId`, and returns the path of the created savepoint.
+这将触发 ID 为`：jobId` 和 YARN 应用程序 ID `：yarnAppId`的作业的 Savepoint，并返回创建的 Savepoint
的路径。
- Cancel Job with Savepoint
+ 使用 Savepoint 取消作业
{% highlight shell %}
$ bin/flink cancel -s [:targetDirectory] :jobId
{% endhighlight %}
-This will atomically trigger a savepoint for the job with ID `:jobid` and
cancel the job. Furthermore, you can specify a target file system directory to
store the savepoint in. The directory needs to
[GitHub] [flink] klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh] Translate Savepoints page into Chinese
klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh]
Translate Savepoints page into Chinese
URL: https://github.com/apache/flink/pull/8300#discussion_r299972216
##
File path: docs/ops/state/savepoints.zh.md
##
@@ -78,160 +68,162 @@ source-id | State of StatefulSource
mapper-id | State of StatefulMapper
{% endhighlight %}
-In the above example, the print sink is stateless and hence not part of the
savepoint state. By default, we try to map each entry of the savepoint back to
the new program.
+在上面的示例中，print sink 是无状态的，因此不是 Savepoint 状态的一部分。默认情况下，我们尝试将 Savepoint
的每个条目映射回新程序。
-## Operations
+## 算子
-You can use the [command line client]({{ site.baseurl
}}/ops/cli.html#savepoints) to *trigger savepoints*, *cancel a job with a
savepoint*, *resume from savepoints*, and *dispose savepoints*.
+你可以使用[命令行客户端]({{site.baseurl}}/zh/ops/cli.html#Savepoint)来*触发 Savepoint*，*触发
Savepoint 并取消作业*，*从 Savepoint*恢复，以及*删除 Savepoint*。
Review comment:
```suggestion
你可以使用[命令行客户端]({{site.baseurl}}/zh/ops/cli.html#Savepoint)来*触发 Savepoint*，*触发
Savepoint 并取消作业*，*从 Savepoint* 恢复，以及*删除 Savepoint*。
```
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[GitHub] [flink] klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh] Translate Savepoints page into Chinese
klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh]
Translate Savepoints page into Chinese
URL: https://github.com/apache/flink/pull/8300#discussion_r299972739
##
File path: docs/ops/state/savepoints.zh.md
##
@@ -78,160 +68,162 @@ source-id | State of StatefulSource
mapper-id | State of StatefulMapper
{% endhighlight %}
-In the above example, the print sink is stateless and hence not part of the
savepoint state. By default, we try to map each entry of the savepoint back to
the new program.
+在上面的示例中，print sink 是无状态的，因此不是 Savepoint 状态的一部分。默认情况下，我们尝试将 Savepoint
的每个条目映射回新程序。
-## Operations
+## 算子
-You can use the [command line client]({{ site.baseurl
}}/ops/cli.html#savepoints) to *trigger savepoints*, *cancel a job with a
savepoint*, *resume from savepoints*, and *dispose savepoints*.
+你可以使用[命令行客户端]({{site.baseurl}}/zh/ops/cli.html#Savepoint)来*触发 Savepoint*，*触发
Savepoint 并取消作业*，*从 Savepoint*恢复，以及*删除 Savepoint*。
-With Flink >= 1.2.0 it is also possible to *resume from savepoints* using the
webui.
+从 Flink 1.2.0 开始，还可以使用 webui *从 Savepoint 恢复*。
-### Triggering Savepoints
+### 触发 Savepoint
-When triggering a savepoint, a new savepoint directory is created where the
data as well as the meta data will be stored. The location of this directory
can be controlled by [configuring a default target directory](#configuration)
or by specifying a custom target directory with the trigger commands (see the
[`:targetDirectory` argument](#trigger-a-savepoint)).
+当触发 Savepoint 时，将创建一个新的 Savepoint
目录，其中存储数据和元数据。可以通过[配置默认目标目录](#configuration)或使用触发器命令指定自定义目标目录(参见[`:targetDirectory
`参数](#trigger-a-savepoint)来控制该目录的位置。
-Attention: The target directory has to be a location
accessible by both the JobManager(s) and TaskManager(s) e.g. a location on a
distributed file-system.
+注意:目标目录必须是 JobManager(s) 和 TaskManager(s)
都可以访问的位置，例如分布式文件系统上的位置。
-For example with a `FsStateBackend` or `RocksDBStateBackend`:
+例如，使用 `FsStateBackend` 或 `RocksDBStateBackend` ：
{% highlight shell %}
-# Savepoint target directory
-/savepoints/
+# Savepoint 目标目录
+/Savepoint/
-# Savepoint directory
-/savepoints/savepoint-:shortjobid-:savepointid/
+# Savepoint 目录
+/Savepoint/savepoint-:shortjobid-:savepointid/
-# Savepoint file contains the checkpoint meta data
-/savepoints/savepoint-:shortjobid-:savepointid/_metadata
+# Savepoint 文件包含 Checkpoint元数据
+/Savepoint/savepoint-:shortjobid-:savepointid/_metadata
-# Savepoint state
-/savepoints/savepoint-:shortjobid-:savepointid/...
+# Savepoint 状态
+/Savepoint/savepoint-:shortjobid-:savepointid/...
{% endhighlight %}
- Note:
-Although it looks as if the savepoints may be moved, it is currently not
possible due to absolute paths in the _metadata file.
-Please follow https://issues.apache.org/jira/browse/FLINK-5778;>FLINK-5778 for
progress on lifting this restriction.
+ 注意:
+虽然看起来好像可以移动 Savepoint ，但由于 _metadata 中保存的是绝对路径，因此暂时不支持。
Review comment:
```suggestion
虽然看起来好像可以移动 Savepoint ，但由于 _metadata 中保存的是绝对路径，因此暂时不支持。
```
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[GitHub] [flink] klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh] Translate Savepoints page into Chinese
klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh]
Translate Savepoints page into Chinese
URL: https://github.com/apache/flink/pull/8300#discussion_r26837
##
File path: docs/ops/state/savepoints.zh.md
##
@@ -25,32 +25,22 @@ under the License.
* toc
{:toc}
-## What is a Savepoint? How is a Savepoint different from a Checkpoint?
+## 什么是 Savepoint ？ Savepoint 与 Checkpoint 有什么不同？
-A Savepoint is a consistent image of the execution state of a streaming job,
created via Flink's [checkpointing mechanism]({{ site.baseurl
}}/internals/stream_checkpointing.html). You can use Savepoints to
stop-and-resume, fork,
-or update your Flink jobs. Savepoints consist of two parts: a directory with
(typically large) binary files on stable storage (e.g. HDFS, S3, ...) and a
(relatively small) meta data file. The files on stable storage represent the
net data of the job's execution state
-image. The meta data file of a Savepoint contains (primarily) pointers to all
files on stable storage that are part of the Savepoint, in form of absolute
paths.
+Savepoint 是依据 Flink [checkpointing 机制]({{ site.baseurl
}}/internals/stream_checkpointing.html)所创建的流作业执行状态的一致镜像。 你可以使用 Savepoint 进行
Flink 作业的停止与重启、fork或者更新。 Savepoint 由两部分组成：稳定存储（列入 HDFS，S3，...)
上包含二进制文件的目录（通常很大），和元数据文件（相对较小）。 稳定存储上的文件表示作业执行状态的数据镜像。 Savepoint
的元数据文件以（绝对路径）的形式包含（主要）指向作为 Savepoint 一部分的稳定存储上的所有文件的指针。
-Attention: In order to allow upgrades between programs and
Flink versions, it is important to check out the following section about assigning IDs to your operators.
+注意: 为了允许程序和 Flink 版本之间的升级，请务必查看以下有关分配算子 ID 的部分 。
+从概念上讲， Flink 的 Savepoint 与 Checkpoint 的不同之处类似于传统数据库中的备份与恢复日志之间的差异。 Checkpoint
的主要目的是为意外失败的作为提供恢复机制。 Checkpoint 的生命周期由 Flink 管理，即 Flink 创建，管理和删除 Checkpoint -
无需用户交互。 作为一种恢复和定期触发的方法，Checkpoint 实现有两个设计目标：i）轻量级创建和 ii）尽可能快地恢复。
可能会利用某些特定的属性来达到这个，例如， 工作代码在执行尝试之间不会改变。 在用户终止作业后，通常会删除 Checkpoint（除非明确配置为保留的
Checkpoint）。
Review comment:
```suggestion
从概念上讲， Flink 的 Savepoint 与 Checkpoint 的不同之处类似于传统数据库中的备份与恢复日志之间的差异。
Checkpoint 的主要目的是为意外失败的作业提供恢复机制。 Checkpoint 的生命周期由 Flink 管理，即 Flink 创建，管理和删除
Checkpoint - 无需用户交互。 作为一种恢复和定期触发的方法，Checkpoint 实现有两个设计目标：i）轻量级创建和 ii）尽可能快地恢复。
可能会利用某些特定的属性来达到这个，例如， 工作代码在执行尝试之间不会改变。 在用户终止作业后，通常会删除 Checkpoint（除非明确配置为保留的
Checkpoint）。
```
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[GitHub] [flink] klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh] Translate Savepoints page into Chinese
klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh]
Translate Savepoints page into Chinese
URL: https://github.com/apache/flink/pull/8300#discussion_r34210
##
File path: docs/ops/state/savepoints.zh.md
##
@@ -78,160 +68,162 @@ source-id | State of StatefulSource
mapper-id | State of StatefulMapper
{% endhighlight %}
-In the above example, the print sink is stateless and hence not part of the
savepoint state. By default, we try to map each entry of the savepoint back to
the new program.
+在上面的示例中，print sink 是无状态的，因此不是 Savepoint 状态的一部分。默认情况下，我们尝试将 Savepoint
的每个条目映射回新程序。
-## Operations
+## 算子
-You can use the [command line client]({{ site.baseurl
}}/ops/cli.html#savepoints) to *trigger savepoints*, *cancel a job with a
savepoint*, *resume from savepoints*, and *dispose savepoints*.
+你可以使用[命令行客户端]({{site.baseurl}}/zh/ops/cli.html#Savepoint)来*触发 Savepoint*，*触发
Savepoint 并取消作业*，*从 Savepoint*恢复，以及*删除 Savepoint*。
-With Flink >= 1.2.0 it is also possible to *resume from savepoints* using the
webui.
+从 Flink 1.2.0 开始，还可以使用 webui *从 Savepoint 恢复*。
-### Triggering Savepoints
+### 触发 Savepoint
-When triggering a savepoint, a new savepoint directory is created where the
data as well as the meta data will be stored. The location of this directory
can be controlled by [configuring a default target directory](#configuration)
or by specifying a custom target directory with the trigger commands (see the
[`:targetDirectory` argument](#trigger-a-savepoint)).
+当触发 Savepoint 时，将创建一个新的 Savepoint
目录，其中存储数据和元数据。可以通过[配置默认目标目录](#configuration)或使用触发器命令指定自定义目标目录(参见[`:targetDirectory
`参数](#trigger-a-savepoint)来控制该目录的位置。
-Attention: The target directory has to be a location
accessible by both the JobManager(s) and TaskManager(s) e.g. a location on a
distributed file-system.
+注意:目标目录必须是 JobManager(s) 和 TaskManager(s)
都可以访问的位置，例如分布式文件系统上的位置。
-For example with a `FsStateBackend` or `RocksDBStateBackend`:
+例如，使用 `FsStateBackend` 或 `RocksDBStateBackend` ：
{% highlight shell %}
-# Savepoint target directory
-/savepoints/
+# Savepoint 目标目录
+/Savepoint/
-# Savepoint directory
-/savepoints/savepoint-:shortjobid-:savepointid/
+# Savepoint 目录
+/Savepoint/savepoint-:shortjobid-:savepointid/
-# Savepoint file contains the checkpoint meta data
-/savepoints/savepoint-:shortjobid-:savepointid/_metadata
+# Savepoint 文件包含 Checkpoint元数据
+/Savepoint/savepoint-:shortjobid-:savepointid/_metadata
-# Savepoint state
-/savepoints/savepoint-:shortjobid-:savepointid/...
+# Savepoint 状态
+/Savepoint/savepoint-:shortjobid-:savepointid/...
{% endhighlight %}
- Note:
-Although it looks as if the savepoints may be moved, it is currently not
possible due to absolute paths in the _metadata file.
-Please follow https://issues.apache.org/jira/browse/FLINK-5778;>FLINK-5778 for
progress on lifting this restriction.
+ 注意:
+虽然看起来好像可以移动 Savepoint ，但由于 _metadata 中保存的是绝对路径，因此暂时不支持。
+请按照https://issues.apache.org/jira/browse/FLINK-5778;> FLINK-5778
了解取消此限制的进度。
-
-Note that if you use the `MemoryStateBackend`, metadata *and* savepoint state
will be stored in the `_metadata` file. Since it is self-contained, you may
move the file and restore from any location.
+请注意，如果使用 `MemoryStateBackend`，则元数据*和* Savepoint 状态将存储在`_metadata`文件中。
由于它是自包含的，你可以移动文件并从任何位置恢复。
- Attention: It is discouraged to move or delete the last
savepoint of a running job, because this might interfere with failure-recovery.
Savepoints have side-effects on exactly-once sinks, therefore
- to ensure exactly-once semantics, if there is no checkpoint after the last
savepoint, the savepoint will be used for recovery.
+ 注意: 不建议移动或删除正在运行作业的最后一个 Savepoint
，因为这可能会干扰故障恢复。因此，Savepoint 对精确一次的接收器有副作用，为了确保精确一次的语义，如果在最后一个 Savepoint 之后没有
Checkpoint ，那么将使用 Savepoint 进行恢复。
- Trigger a Savepoint
+
+ 触发 Savepoint
{% highlight shell %}
$ bin/flink savepoint :jobId [:targetDirectory]
{% endhighlight %}
-This will trigger a savepoint for the job with ID `:jobId`, and returns the
path of the created savepoint. You need this path to restore and dispose
savepoints.
+这将触发ID为`：jobId`的作业的Savepoint，并返回创建的 Savepoint 的路径。 你需要此路径来还原和部署 Savepoint 。
- Trigger a Savepoint with YARN
+ 使用 YARN 触发 Savepoint
{% highlight shell %}
$ bin/flink savepoint :jobId [:targetDirectory] -yid :yarnAppId
{% endhighlight %}
-This will trigger a savepoint for the job with ID `:jobId` and YARN
application ID `:yarnAppId`, and returns the path of the created savepoint.
+这将触发 ID 为`：jobId` 和 YARN 应用程序 ID `：yarnAppId`的作业的 Savepoint，并返回创建的 Savepoint
的路径。
- Cancel Job with Savepoint
+ 使用 Savepoint 取消作业
{% highlight shell %}
$ bin/flink cancel -s [:targetDirectory] :jobId
{% endhighlight %}
-This will atomically trigger a savepoint for the job with ID `:jobid` and
cancel the job. Furthermore, you can specify a target file system directory to
store the savepoint in. The directory needs to
[GitHub] [flink] klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh] Translate Savepoints page into Chinese
klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh]
Translate Savepoints page into Chinese
URL: https://github.com/apache/flink/pull/8300#discussion_r299972911
##
File path: docs/ops/state/savepoints.zh.md
##
@@ -78,160 +68,162 @@ source-id | State of StatefulSource
mapper-id | State of StatefulMapper
{% endhighlight %}
-In the above example, the print sink is stateless and hence not part of the
savepoint state. By default, we try to map each entry of the savepoint back to
the new program.
+在上面的示例中，print sink 是无状态的，因此不是 Savepoint 状态的一部分。默认情况下，我们尝试将 Savepoint
的每个条目映射回新程序。
-## Operations
+## 算子
-You can use the [command line client]({{ site.baseurl
}}/ops/cli.html#savepoints) to *trigger savepoints*, *cancel a job with a
savepoint*, *resume from savepoints*, and *dispose savepoints*.
+你可以使用[命令行客户端]({{site.baseurl}}/zh/ops/cli.html#Savepoint)来*触发 Savepoint*，*触发
Savepoint 并取消作业*，*从 Savepoint*恢复，以及*删除 Savepoint*。
-With Flink >= 1.2.0 it is also possible to *resume from savepoints* using the
webui.
+从 Flink 1.2.0 开始，还可以使用 webui *从 Savepoint 恢复*。
-### Triggering Savepoints
+### 触发 Savepoint
-When triggering a savepoint, a new savepoint directory is created where the
data as well as the meta data will be stored. The location of this directory
can be controlled by [configuring a default target directory](#configuration)
or by specifying a custom target directory with the trigger commands (see the
[`:targetDirectory` argument](#trigger-a-savepoint)).
+当触发 Savepoint 时，将创建一个新的 Savepoint
目录，其中存储数据和元数据。可以通过[配置默认目标目录](#configuration)或使用触发器命令指定自定义目标目录(参见[`:targetDirectory
`参数](#trigger-a-savepoint)来控制该目录的位置。
-Attention: The target directory has to be a location
accessible by both the JobManager(s) and TaskManager(s) e.g. a location on a
distributed file-system.
+注意:目标目录必须是 JobManager(s) 和 TaskManager(s)
都可以访问的位置，例如分布式文件系统上的位置。
-For example with a `FsStateBackend` or `RocksDBStateBackend`:
+例如，使用 `FsStateBackend` 或 `RocksDBStateBackend` ：
{% highlight shell %}
-# Savepoint target directory
-/savepoints/
+# Savepoint 目标目录
+/Savepoint/
-# Savepoint directory
-/savepoints/savepoint-:shortjobid-:savepointid/
+# Savepoint 目录
+/Savepoint/savepoint-:shortjobid-:savepointid/
-# Savepoint file contains the checkpoint meta data
-/savepoints/savepoint-:shortjobid-:savepointid/_metadata
+# Savepoint 文件包含 Checkpoint元数据
+/Savepoint/savepoint-:shortjobid-:savepointid/_metadata
-# Savepoint state
-/savepoints/savepoint-:shortjobid-:savepointid/...
+# Savepoint 状态
+/Savepoint/savepoint-:shortjobid-:savepointid/...
{% endhighlight %}
- Note:
-Although it looks as if the savepoints may be moved, it is currently not
possible due to absolute paths in the _metadata file.
-Please follow https://issues.apache.org/jira/browse/FLINK-5778;>FLINK-5778 for
progress on lifting this restriction.
+ 注意:
+虽然看起来好像可以移动 Savepoint ，但由于 _metadata 中保存的是绝对路径，因此暂时不支持。
+请按照https://issues.apache.org/jira/browse/FLINK-5778;> FLINK-5778
了解取消此限制的进度。
-
-Note that if you use the `MemoryStateBackend`, metadata *and* savepoint state
will be stored in the `_metadata` file. Since it is self-contained, you may
move the file and restore from any location.
+请注意，如果使用 `MemoryStateBackend`，则元数据*和* Savepoint 状态将存储在`_metadata`文件中。
由于它是自包含的，你可以移动文件并从任何位置恢复。
Review comment:
```suggestion
请注意，如果使用 `MemoryStateBackend`，则元数据*和* Savepoint 状态将存储在 `_metadata` 文件中。
由于它是自包含的，你可以移动文件并从任何位置恢复。
```
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[GitHub] [flink] klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh] Translate Savepoints page into Chinese
klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh]
Translate Savepoints page into Chinese
URL: https://github.com/apache/flink/pull/8300#discussion_r299973326
##
File path: docs/ops/state/savepoints.zh.md
##
@@ -78,160 +68,162 @@ source-id | State of StatefulSource
mapper-id | State of StatefulMapper
{% endhighlight %}
-In the above example, the print sink is stateless and hence not part of the
savepoint state. By default, we try to map each entry of the savepoint back to
the new program.
+在上面的示例中，print sink 是无状态的，因此不是 Savepoint 状态的一部分。默认情况下，我们尝试将 Savepoint
的每个条目映射回新程序。
-## Operations
+## 算子
-You can use the [command line client]({{ site.baseurl
}}/ops/cli.html#savepoints) to *trigger savepoints*, *cancel a job with a
savepoint*, *resume from savepoints*, and *dispose savepoints*.
+你可以使用[命令行客户端]({{site.baseurl}}/zh/ops/cli.html#Savepoint)来*触发 Savepoint*，*触发
Savepoint 并取消作业*，*从 Savepoint*恢复，以及*删除 Savepoint*。
-With Flink >= 1.2.0 it is also possible to *resume from savepoints* using the
webui.
+从 Flink 1.2.0 开始，还可以使用 webui *从 Savepoint 恢复*。
-### Triggering Savepoints
+### 触发 Savepoint
-When triggering a savepoint, a new savepoint directory is created where the
data as well as the meta data will be stored. The location of this directory
can be controlled by [configuring a default target directory](#configuration)
or by specifying a custom target directory with the trigger commands (see the
[`:targetDirectory` argument](#trigger-a-savepoint)).
+当触发 Savepoint 时，将创建一个新的 Savepoint
目录，其中存储数据和元数据。可以通过[配置默认目标目录](#configuration)或使用触发器命令指定自定义目标目录(参见[`:targetDirectory
`参数](#trigger-a-savepoint)来控制该目录的位置。
-Attention: The target directory has to be a location
accessible by both the JobManager(s) and TaskManager(s) e.g. a location on a
distributed file-system.
+注意:目标目录必须是 JobManager(s) 和 TaskManager(s)
都可以访问的位置，例如分布式文件系统上的位置。
-For example with a `FsStateBackend` or `RocksDBStateBackend`:
+例如，使用 `FsStateBackend` 或 `RocksDBStateBackend` ：
{% highlight shell %}
-# Savepoint target directory
-/savepoints/
+# Savepoint 目标目录
+/Savepoint/
-# Savepoint directory
-/savepoints/savepoint-:shortjobid-:savepointid/
+# Savepoint 目录
+/Savepoint/savepoint-:shortjobid-:savepointid/
-# Savepoint file contains the checkpoint meta data
-/savepoints/savepoint-:shortjobid-:savepointid/_metadata
+# Savepoint 文件包含 Checkpoint元数据
+/Savepoint/savepoint-:shortjobid-:savepointid/_metadata
-# Savepoint state
-/savepoints/savepoint-:shortjobid-:savepointid/...
+# Savepoint 状态
+/Savepoint/savepoint-:shortjobid-:savepointid/...
{% endhighlight %}
- Note:
-Although it looks as if the savepoints may be moved, it is currently not
possible due to absolute paths in the _metadata file.
-Please follow https://issues.apache.org/jira/browse/FLINK-5778;>FLINK-5778 for
progress on lifting this restriction.
+ 注意:
+虽然看起来好像可以移动 Savepoint ，但由于 _metadata 中保存的是绝对路径，因此暂时不支持。
+请按照https://issues.apache.org/jira/browse/FLINK-5778;> FLINK-5778
了解取消此限制的进度。
-
-Note that if you use the `MemoryStateBackend`, metadata *and* savepoint state
will be stored in the `_metadata` file. Since it is self-contained, you may
move the file and restore from any location.
+请注意，如果使用 `MemoryStateBackend`，则元数据*和* Savepoint 状态将存储在`_metadata`文件中。
由于它是自包含的，你可以移动文件并从任何位置恢复。
- Attention: It is discouraged to move or delete the last
savepoint of a running job, because this might interfere with failure-recovery.
Savepoints have side-effects on exactly-once sinks, therefore
- to ensure exactly-once semantics, if there is no checkpoint after the last
savepoint, the savepoint will be used for recovery.
+ 注意: 不建议移动或删除正在运行作业的最后一个 Savepoint
，因为这可能会干扰故障恢复。因此，Savepoint 对精确一次的接收器有副作用，为了确保精确一次的语义，如果在最后一个 Savepoint 之后没有
Checkpoint ，那么将使用 Savepoint 进行恢复。
- Trigger a Savepoint
+
+ 触发 Savepoint
{% highlight shell %}
$ bin/flink savepoint :jobId [:targetDirectory]
{% endhighlight %}
-This will trigger a savepoint for the job with ID `:jobId`, and returns the
path of the created savepoint. You need this path to restore and dispose
savepoints.
+这将触发ID为`：jobId`的作业的Savepoint，并返回创建的 Savepoint 的路径。 你需要此路径来还原和部署 Savepoint 。
Review comment:
```suggestion
这将触发 ID 为 `:jobId` 的作业的 Savepoint，并返回创建的 Savepoint 路径。 你需要此路径来还原和删除
Savepoint 。
```
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[GitHub] [flink] klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh] Translate Savepoints page into Chinese
klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh]
Translate Savepoints page into Chinese
URL: https://github.com/apache/flink/pull/8300#discussion_r30796
##
File path: docs/ops/state/savepoints.zh.md
##
@@ -78,160 +68,162 @@ source-id | State of StatefulSource
mapper-id | State of StatefulMapper
{% endhighlight %}
-In the above example, the print sink is stateless and hence not part of the
savepoint state. By default, we try to map each entry of the savepoint back to
the new program.
+在上面的示例中，print sink 是无状态的，因此不是 Savepoint 状态的一部分。默认情况下，我们尝试将 Savepoint
的每个条目映射回新程序。
-## Operations
+## 算子
-You can use the [command line client]({{ site.baseurl
}}/ops/cli.html#savepoints) to *trigger savepoints*, *cancel a job with a
savepoint*, *resume from savepoints*, and *dispose savepoints*.
+你可以使用[命令行客户端]({{site.baseurl}}/zh/ops/cli.html#Savepoint)来*触发 Savepoint*，*触发
Savepoint 并取消作业*，*从 Savepoint*恢复，以及*删除 Savepoint*。
-With Flink >= 1.2.0 it is also possible to *resume from savepoints* using the
webui.
+从 Flink 1.2.0 开始，还可以使用 webui *从 Savepoint 恢复*。
-### Triggering Savepoints
+### 触发 Savepoint
-When triggering a savepoint, a new savepoint directory is created where the
data as well as the meta data will be stored. The location of this directory
can be controlled by [configuring a default target directory](#configuration)
or by specifying a custom target directory with the trigger commands (see the
[`:targetDirectory` argument](#trigger-a-savepoint)).
+当触发 Savepoint 时，将创建一个新的 Savepoint
目录，其中存储数据和元数据。可以通过[配置默认目标目录](#configuration)或使用触发器命令指定自定义目标目录(参见[`:targetDirectory
`参数](#trigger-a-savepoint)来控制该目录的位置。
-Attention: The target directory has to be a location
accessible by both the JobManager(s) and TaskManager(s) e.g. a location on a
distributed file-system.
+注意:目标目录必须是 JobManager(s) 和 TaskManager(s)
都可以访问的位置，例如分布式文件系统上的位置。
-For example with a `FsStateBackend` or `RocksDBStateBackend`:
+例如，使用 `FsStateBackend` 或 `RocksDBStateBackend` ：
Review comment:
what about "以 `FsStateBackend` 或 `RocksDBStateBackend` 为例 "?
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[GitHub] [flink] klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh] Translate Savepoints page into Chinese
klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh]
Translate Savepoints page into Chinese
URL: https://github.com/apache/flink/pull/8300#discussion_r299973631
##
File path: docs/ops/state/savepoints.zh.md
##
@@ -78,160 +68,162 @@ source-id | State of StatefulSource
mapper-id | State of StatefulMapper
{% endhighlight %}
-In the above example, the print sink is stateless and hence not part of the
savepoint state. By default, we try to map each entry of the savepoint back to
the new program.
+在上面的示例中，print sink 是无状态的，因此不是 Savepoint 状态的一部分。默认情况下，我们尝试将 Savepoint
的每个条目映射回新程序。
-## Operations
+## 算子
-You can use the [command line client]({{ site.baseurl
}}/ops/cli.html#savepoints) to *trigger savepoints*, *cancel a job with a
savepoint*, *resume from savepoints*, and *dispose savepoints*.
+你可以使用[命令行客户端]({{site.baseurl}}/zh/ops/cli.html#Savepoint)来*触发 Savepoint*，*触发
Savepoint 并取消作业*，*从 Savepoint*恢复，以及*删除 Savepoint*。
-With Flink >= 1.2.0 it is also possible to *resume from savepoints* using the
webui.
+从 Flink 1.2.0 开始，还可以使用 webui *从 Savepoint 恢复*。
-### Triggering Savepoints
+### 触发 Savepoint
-When triggering a savepoint, a new savepoint directory is created where the
data as well as the meta data will be stored. The location of this directory
can be controlled by [configuring a default target directory](#configuration)
or by specifying a custom target directory with the trigger commands (see the
[`:targetDirectory` argument](#trigger-a-savepoint)).
+当触发 Savepoint 时，将创建一个新的 Savepoint
目录，其中存储数据和元数据。可以通过[配置默认目标目录](#configuration)或使用触发器命令指定自定义目标目录(参见[`:targetDirectory
`参数](#trigger-a-savepoint)来控制该目录的位置。
-Attention: The target directory has to be a location
accessible by both the JobManager(s) and TaskManager(s) e.g. a location on a
distributed file-system.
+注意:目标目录必须是 JobManager(s) 和 TaskManager(s)
都可以访问的位置，例如分布式文件系统上的位置。
-For example with a `FsStateBackend` or `RocksDBStateBackend`:
+例如，使用 `FsStateBackend` 或 `RocksDBStateBackend` ：
{% highlight shell %}
-# Savepoint target directory
-/savepoints/
+# Savepoint 目标目录
+/Savepoint/
-# Savepoint directory
-/savepoints/savepoint-:shortjobid-:savepointid/
+# Savepoint 目录
+/Savepoint/savepoint-:shortjobid-:savepointid/
-# Savepoint file contains the checkpoint meta data
-/savepoints/savepoint-:shortjobid-:savepointid/_metadata
+# Savepoint 文件包含 Checkpoint元数据
+/Savepoint/savepoint-:shortjobid-:savepointid/_metadata
-# Savepoint state
-/savepoints/savepoint-:shortjobid-:savepointid/...
+# Savepoint 状态
+/Savepoint/savepoint-:shortjobid-:savepointid/...
{% endhighlight %}
- Note:
-Although it looks as if the savepoints may be moved, it is currently not
possible due to absolute paths in the _metadata file.
-Please follow https://issues.apache.org/jira/browse/FLINK-5778;>FLINK-5778 for
progress on lifting this restriction.
+ 注意:
+虽然看起来好像可以移动 Savepoint ，但由于 _metadata 中保存的是绝对路径，因此暂时不支持。
+请按照https://issues.apache.org/jira/browse/FLINK-5778;> FLINK-5778
了解取消此限制的进度。
-
-Note that if you use the `MemoryStateBackend`, metadata *and* savepoint state
will be stored in the `_metadata` file. Since it is self-contained, you may
move the file and restore from any location.
+请注意，如果使用 `MemoryStateBackend`，则元数据*和* Savepoint 状态将存储在`_metadata`文件中。
由于它是自包含的，你可以移动文件并从任何位置恢复。
- Attention: It is discouraged to move or delete the last
savepoint of a running job, because this might interfere with failure-recovery.
Savepoints have side-effects on exactly-once sinks, therefore
- to ensure exactly-once semantics, if there is no checkpoint after the last
savepoint, the savepoint will be used for recovery.
+ 注意: 不建议移动或删除正在运行作业的最后一个 Savepoint
，因为这可能会干扰故障恢复。因此，Savepoint 对精确一次的接收器有副作用，为了确保精确一次的语义，如果在最后一个 Savepoint 之后没有
Checkpoint ，那么将使用 Savepoint 进行恢复。
- Trigger a Savepoint
+
+ 触发 Savepoint
{% highlight shell %}
$ bin/flink savepoint :jobId [:targetDirectory]
{% endhighlight %}
-This will trigger a savepoint for the job with ID `:jobId`, and returns the
path of the created savepoint. You need this path to restore and dispose
savepoints.
+这将触发ID为`：jobId`的作业的Savepoint，并返回创建的 Savepoint 的路径。 你需要此路径来还原和部署 Savepoint 。
- Trigger a Savepoint with YARN
+ 使用 YARN 触发 Savepoint
{% highlight shell %}
$ bin/flink savepoint :jobId [:targetDirectory] -yid :yarnAppId
{% endhighlight %}
-This will trigger a savepoint for the job with ID `:jobId` and YARN
application ID `:yarnAppId`, and returns the path of the created savepoint.
+这将触发 ID 为`：jobId` 和 YARN 应用程序 ID `：yarnAppId`的作业的 Savepoint，并返回创建的 Savepoint
的路径。
Review comment:
```suggestion
这将触发 ID 为 `:jobId` 和 YARN 应用程序 ID `:yarnAppId` 的作业的 Savepoint，并返回创建的
Savepoint 的路径。
```
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[GitHub] [flink] klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh] Translate Savepoints page into Chinese
klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh]
Translate Savepoints page into Chinese
URL: https://github.com/apache/flink/pull/8300#discussion_r299971025
##
File path: docs/ops/state/savepoints.zh.md
##
@@ -25,32 +25,22 @@ under the License.
* toc
{:toc}
-## What is a Savepoint? How is a Savepoint different from a Checkpoint?
+## 什么是 Savepoint ？ Savepoint 与 Checkpoint 有什么不同？
-A Savepoint is a consistent image of the execution state of a streaming job,
created via Flink's [checkpointing mechanism]({{ site.baseurl
}}/internals/stream_checkpointing.html). You can use Savepoints to
stop-and-resume, fork,
-or update your Flink jobs. Savepoints consist of two parts: a directory with
(typically large) binary files on stable storage (e.g. HDFS, S3, ...) and a
(relatively small) meta data file. The files on stable storage represent the
net data of the job's execution state
-image. The meta data file of a Savepoint contains (primarily) pointers to all
files on stable storage that are part of the Savepoint, in form of absolute
paths.
+Savepoint 是依据 Flink [checkpointing 机制]({{ site.baseurl
}}/internals/stream_checkpointing.html)所创建的流作业执行状态的一致镜像。 你可以使用 Savepoint 进行
Flink 作业的停止与重启、fork或者更新。 Savepoint 由两部分组成：稳定存储（列入 HDFS，S3，...)
上包含二进制文件的目录（通常很大），和元数据文件（相对较小）。 稳定存储上的文件表示作业执行状态的数据镜像。 Savepoint
的元数据文件以（绝对路径）的形式包含（主要）指向作为 Savepoint 一部分的稳定存储上的所有文件的指针。
-Attention: In order to allow upgrades between programs and
Flink versions, it is important to check out the following section about assigning IDs to your operators.
+注意: 为了允许程序和 Flink 版本之间的升级，请务必查看以下有关分配算子 ID 的部分 。
+从概念上讲， Flink 的 Savepoint 与 Checkpoint 的不同之处类似于传统数据库中的备份与恢复日志之间的差异。 Checkpoint
的主要目的是为意外失败的作为提供恢复机制。 Checkpoint 的生命周期由 Flink 管理，即 Flink 创建，管理和删除 Checkpoint -
无需用户交互。 作为一种恢复和定期触发的方法，Checkpoint 实现有两个设计目标：i）轻量级创建和 ii）尽可能快地恢复。
可能会利用某些特定的属性来达到这个，例如， 工作代码在执行尝试之间不会改变。 在用户终止作业后，通常会删除 Checkpoint（除非明确配置为保留的
Checkpoint）。
-Conceptually, Flink's Savepoints are different from Checkpoints in a similar
way that backups are different from recovery logs in traditional database
systems. The primary purpose of Checkpoints is to provide a recovery mechanism
in case of
-unexpected job failures. A Checkpoint's lifecycle is managed by Flink, i.e. a
Checkpoint is created, owned, and released by Flink - without user interaction.
As a method of recovery and being periodically triggered, two main
-design goals for the Checkpoint implementation are i) being as lightweight to
create and ii) being as fast to restore from as possible. Optimizations towards
those goals can exploit certain properties, e.g. that the job code
-doesn't change between the execution attempts. Checkpoints are usually dropped
after the job was terminated by the user (except if explicitly configured as
retained Checkpoints).
+ 与此相反、Savepoint 由用户创建，拥有和删除。 他们的用例是计划的，手动备份和恢复。 例如，升级 Flink
版本，调整用户逻辑，改变并行度，以及进行红蓝部署等。 当然，Savepoint 必须在终止工作后继续存在。 从概念上讲，Savepoint
的生成，恢复成本可能更高一些，Savepoint 更多地关注可移植性和对前面提到的作业更改的支持。
-In contrast to all this, Savepoints are created, owned, and deleted by the
user. Their use-case is for planned, manual backup and resume. For example,
this could be an update of your Flink version, changing your job graph,
-changing parallelism, forking a second job like for a red/blue deployment, and
so on. Of course, Savepoints must survive job termination. Conceptually,
Savepoints can be a bit more expensive to produce and restore and focus
-more on portability and support for the previously mentioned changes to the
job.
+除去这些概念上的差异，Checkpoint 和 Savepoint
的当前实现基本上使用相同的代码并生成相同的格式。然而，目前有一个例外，我们可能会在未来引入更多的差异。例外情况是使用 RocksDB 状态后端的增量
Checkpoint。他们使用了一些 RocksDB 内部格式，而不是 Flink 的本机 Savepoint 格式。这使他们成为了与 Savepoint
相比，更轻量级的 Checkpoint 机制的第一个实例。
-Those conceptual differences aside, the current implementations of Checkpoints
and Savepoints are basically using the same code and produce the same format.
However, there is currently one exception from this, and we might
-introduce more differences in the future. The exception are incremental
checkpoints with the RocksDB state backend. They are using some RocksDB
internal format instead of Flink’s native savepoint format. This makes them the
-first instance of a more lightweight checkpointing mechanism, compared to
Savepoints.
+## 分配算子ID
-## Assigning Operator IDs
-
-It is **highly recommended** that you adjust your programs as described in
this section in order to be able to upgrade your programs in the future. The
main required change is to manually specify operator IDs via the
**`uid(String)`** method. These IDs are used to scope the state of each
operator.
+**强烈建议**你按照本节所述调整你的程序，以便将来能够升级你的程序。主要通过**`uid(String)`**方法手动指定算子 ID 。这些 ID
将用于恢复每个算子的状态。
Review comment:
```suggestion
**强烈建议**你按照本节所述调整你的程序，以便将来能够升级你的程序。主要通过 **`uid(String)`** 方法手动指定算子 ID 。这些 ID
将用于恢复每个算子的状态。
```
This is an
[GitHub] [flink] klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh] Translate Savepoints page into Chinese
klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh]
Translate Savepoints page into Chinese
URL: https://github.com/apache/flink/pull/8300#discussion_r299971731
##
File path: docs/ops/state/savepoints.zh.md
##
@@ -65,11 +55,11 @@ DataStream stream = env.
.print(); // Auto-generated ID
{% endhighlight %}
-If you don't specify the IDs manually they will be generated automatically.
You can automatically restore from the savepoint as long as these IDs do not
change. The generated IDs depend on the structure of your program and are
sensitive to program changes. Therefore, it is highly recommended to assign
these IDs manually.
+如果不手动指定 ID ，则会自动生成 ID 。只要这些 ID 不变，就可以从 Savepoint 自动恢复。生成的 ID
取决于程序的结构，并且对程序更改很敏感。因此，强烈建议手动分配这些 ID 。
-### Savepoint State
+### Savepoint 状态
-You can think of a savepoint as holding a map of `Operator ID -> State` for
each stateful operator:
+你可以将 Savepoint 想象为为每个有状态的算子保存一个映射“算子 ID ->状态”:
Review comment:
```suggestion
你可以将 Savepoint 想象为为每个有状态的算子保存一个映射“算子 ID ->状态”:
```
```suggestion
你可以将 Savepoint 想象为每个有状态的算子保存一个映射“算子 ID ->状态”:
```
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[GitHub] [flink] klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh] Translate Savepoints page into Chinese
klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh]
Translate Savepoints page into Chinese
URL: https://github.com/apache/flink/pull/8300#discussion_r299970518
##
File path: docs/ops/state/savepoints.zh.md
##
@@ -25,32 +25,22 @@ under the License.
* toc
{:toc}
-## What is a Savepoint? How is a Savepoint different from a Checkpoint?
+## 什么是 Savepoint ？ Savepoint 与 Checkpoint 有什么不同？
-A Savepoint is a consistent image of the execution state of a streaming job,
created via Flink's [checkpointing mechanism]({{ site.baseurl
}}/internals/stream_checkpointing.html). You can use Savepoints to
stop-and-resume, fork,
-or update your Flink jobs. Savepoints consist of two parts: a directory with
(typically large) binary files on stable storage (e.g. HDFS, S3, ...) and a
(relatively small) meta data file. The files on stable storage represent the
net data of the job's execution state
-image. The meta data file of a Savepoint contains (primarily) pointers to all
files on stable storage that are part of the Savepoint, in form of absolute
paths.
+Savepoint 是依据 Flink [checkpointing 机制]({{ site.baseurl
}}/internals/stream_checkpointing.html)所创建的流作业执行状态的一致镜像。 你可以使用 Savepoint 进行
Flink 作业的停止与重启、fork或者更新。 Savepoint 由两部分组成：稳定存储（列入 HDFS，S3，...)
上包含二进制文件的目录（通常很大），和元数据文件（相对较小）。 稳定存储上的文件表示作业执行状态的数据镜像。 Savepoint
的元数据文件以（绝对路径）的形式包含（主要）指向作为 Savepoint 一部分的稳定存储上的所有文件的指针。
-Attention: In order to allow upgrades between programs and
Flink versions, it is important to check out the following section about assigning IDs to your operators.
+注意: 为了允许程序和 Flink 版本之间的升级，请务必查看以下有关分配算子 ID 的部分 。
+从概念上讲， Flink 的 Savepoint 与 Checkpoint 的不同之处类似于传统数据库中的备份与恢复日志之间的差异。 Checkpoint
的主要目的是为意外失败的作为提供恢复机制。 Checkpoint 的生命周期由 Flink 管理，即 Flink 创建，管理和删除 Checkpoint -
无需用户交互。 作为一种恢复和定期触发的方法，Checkpoint 实现有两个设计目标：i）轻量级创建和 ii）尽可能快地恢复。
可能会利用某些特定的属性来达到这个，例如， 工作代码在执行尝试之间不会改变。 在用户终止作业后，通常会删除 Checkpoint（除非明确配置为保留的
Checkpoint）。
-Conceptually, Flink's Savepoints are different from Checkpoints in a similar
way that backups are different from recovery logs in traditional database
systems. The primary purpose of Checkpoints is to provide a recovery mechanism
in case of
-unexpected job failures. A Checkpoint's lifecycle is managed by Flink, i.e. a
Checkpoint is created, owned, and released by Flink - without user interaction.
As a method of recovery and being periodically triggered, two main
-design goals for the Checkpoint implementation are i) being as lightweight to
create and ii) being as fast to restore from as possible. Optimizations towards
those goals can exploit certain properties, e.g. that the job code
-doesn't change between the execution attempts. Checkpoints are usually dropped
after the job was terminated by the user (except if explicitly configured as
retained Checkpoints).
+ 与此相反、Savepoint 由用户创建，拥有和删除。 他们的用例是计划的，手动备份和恢复。 例如，升级 Flink
版本，调整用户逻辑，改变并行度，以及进行红蓝部署等。 当然，Savepoint 必须在终止工作后继续存在。 从概念上讲，Savepoint
的生成，恢复成本可能更高一些，Savepoint 更多地关注可移植性和对前面提到的作业更改的支持。
-In contrast to all this, Savepoints are created, owned, and deleted by the
user. Their use-case is for planned, manual backup and resume. For example,
this could be an update of your Flink version, changing your job graph,
-changing parallelism, forking a second job like for a red/blue deployment, and
so on. Of course, Savepoints must survive job termination. Conceptually,
Savepoints can be a bit more expensive to produce and restore and focus
-more on portability and support for the previously mentioned changes to the
job.
+除去这些概念上的差异，Checkpoint 和 Savepoint
的当前实现基本上使用相同的代码并生成相同的格式。然而，目前有一个例外，我们可能会在未来引入更多的差异。例外情况是使用 RocksDB 状态后端的增量
Checkpoint。他们使用了一些 RocksDB 内部格式，而不是 Flink 的本机 Savepoint 格式。这使他们成为了与 Savepoint
相比，更轻量级的 Checkpoint 机制的第一个实例。
-Those conceptual differences aside, the current implementations of Checkpoints
and Savepoints are basically using the same code and produce the same format.
However, there is currently one exception from this, and we might
-introduce more differences in the future. The exception are incremental
checkpoints with the RocksDB state backend. They are using some RocksDB
internal format instead of Flink’s native savepoint format. This makes them the
-first instance of a more lightweight checkpointing mechanism, compared to
Savepoints.
+## 分配算子ID
Review comment:
```suggestion
## 分配算子 ID
```
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[GitHub] [flink] klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh] Translate Savepoints page into Chinese
klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh]
Translate Savepoints page into Chinese
URL: https://github.com/apache/flink/pull/8300#discussion_r281071068
##
File path: docs/ops/state/savepoints.zh.md
##
@@ -78,160 +68,158 @@ source-id | State of StatefulSource
mapper-id | State of StatefulMapper
{% endhighlight %}
-In the above example, the print sink is stateless and hence not part of the
savepoint state. By default, we try to map each entry of the savepoint back to
the new program.
+在上面的示例中，print sink 是无状态的，因此不是 Savepoint 状态的一部分。默认情况下，我们尝试将 Savepoint
的每个条目映射回新程序。
-## Operations
+## 算子
-You can use the [command line client]({{ site.baseurl
}}/ops/cli.html#savepoints) to *trigger savepoints*, *cancel a job with a
savepoint*, *resume from savepoints*, and *dispose savepoints*.
+你可以使用[命令行客户端]({{site.baseurl}}/zh/ops/cli.html#Savepoint)来*触发 Savepoint
*，*取消具有 Savepoint *的作业，*从 Savepoint *恢复，以及*部署 Savepoint *。
-With Flink >= 1.2.0 it is also possible to *resume from savepoints* using the
webui.
+使用 Flink >= 1.2.0，还可以使用 webui *从 Savepoint 恢复*。
-### Triggering Savepoints
+### 触发 Savepoint
-When triggering a savepoint, a new savepoint directory is created where the
data as well as the meta data will be stored. The location of this directory
can be controlled by [configuring a default target directory](#configuration)
or by specifying a custom target directory with the trigger commands (see the
[`:targetDirectory` argument](#trigger-a-savepoint)).
+当触发 Savepoint 时，将创建一个新的 Savepoint
目录，其中存储数据和元数据。可以通过[配置默认目标目录](#configuration)或使用触发器命令指定自定义目标目录(参见[`:targetDirectory
`参数](#trigger-a-savepoint)来控制该目录的位置。
-Attention: The target directory has to be a location
accessible by both the JobManager(s) and TaskManager(s) e.g. a location on a
distributed file-system.
+注意:目标目录必须是 JobManager(s) 和 TaskManager(s)
都可以访问的位置，例如分布式文件系统上的位置。
-For example with a `FsStateBackend` or `RocksDBStateBackend`:
+例如，使用 `FsStateBackend` 或 `RocksDBStateBackend` ：
{% highlight shell %}
-# Savepoint target directory
-/savepoints/
+# Savepoint 目标目录
+/Savepoint/
-# Savepoint directory
-/savepoints/savepoint-:shortjobid-:savepointid/
+# Savepoint 目录
+/Savepoint/savepoint-:shortjobid-:savepointid/
-# Savepoint file contains the checkpoint meta data
-/savepoints/savepoint-:shortjobid-:savepointid/_metadata
+# Savepoint 文件包含 Checkpoint元数据
+/Savepoint/savepoint-:shortjobid-:savepointid/_metadata
-# Savepoint state
-/savepoints/savepoint-:shortjobid-:savepointid/...
+# Savepoint 状态
+/Savepoint/savepoint-:shortjobid-:savepointid/...
{% endhighlight %}
- Note:
-Although it looks as if the savepoints may be moved, it is currently not
possible due to absolute paths in the _metadata file.
-Please follow https://issues.apache.org/jira/browse/FLINK-5778;>FLINK-5778 for
progress on lifting this restriction.
+ 注意:
+虽然看起来好像可以移动 Savepoint ，但由于 _metadata 文件中的绝对路径，目前无法进行保存。
+请按照https://issues.apache.org/jira/browse/FLINK-5778;> FLINK-5778
了解取消此限制的进度。
-
-Note that if you use the `MemoryStateBackend`, metadata *and* savepoint state
will be stored in the `_metadata` file. Since it is self-contained, you may
move the file and restore from any location.
+请注意，如果使用 `MemoryStateBackend`，则元数据*和* Savepoint 状态将存储在`_metadata`文件中。
由于它是自包含的，你可以移动文件并从任何位置恢复。
- Attention: It is discouraged to move or delete the last
savepoint of a running job, because this might interfere with failure-recovery.
Savepoints have side-effects on exactly-once sinks, therefore
- to ensure exactly-once semantics, if there is no checkpoint after the last
savepoint, the savepoint will be used for recovery.
+ 注意: 不建议移动或删除正在运行作业的最后一个 Savepoint
，因为这可能会干扰故障恢复。因此，Savepoint 对完全一次的接收器有副作用，为了确保精确的一次语义，如果在最后一个 Savepoint 之后没有
Checkpoint ，那么将使用 Savepoint 进行恢复。
- Trigger a Savepoint
+
+ 触发 Savepoint
{% highlight shell %}
$ bin/flink savepoint :jobId [:targetDirectory]
{% endhighlight %}
-This will trigger a savepoint for the job with ID `:jobId`, and returns the
path of the created savepoint. You need this path to restore and dispose
savepoints.
+这将触发ID为`：jobId`的作业的Savepoint，并返回创建的 Savepoint 的路径。 你需要此路径来还原和部署 Savepoint 。
- Trigger a Savepoint with YARN
+ 使用 YARN 触发 Savepoint
{% highlight shell %}
$ bin/flink savepoint :jobId [:targetDirectory] -yid :yarnAppId
{% endhighlight %}
-This will trigger a savepoint for the job with ID `:jobId` and YARN
application ID `:yarnAppId`, and returns the path of the created savepoint.
+这将触发 ID 为`：jobId` 和 YARN 应用程序 ID `：yarnAppId`的作业的 Savepoint，并返回创建的 Savepoint
的路径。
- Cancel Job with Savepoint
+ 使用 Savepoint 取消作业
{% highlight shell %}
$ bin/flink cancel -s [:targetDirectory] :jobId
{% endhighlight %}
-This will atomically trigger a savepoint for the job with ID `:jobid` and
cancel the job. Furthermore, you can specify a target file system directory to
store the savepoint in. The directory
[GitHub] [flink] klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh] Translate Savepoints page into Chinese
klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh]
Translate Savepoints page into Chinese
URL: https://github.com/apache/flink/pull/8300#discussion_r281069265
##
File path: docs/ops/state/savepoints.zh.md
##
@@ -78,160 +68,158 @@ source-id | State of StatefulSource
mapper-id | State of StatefulMapper
{% endhighlight %}
-In the above example, the print sink is stateless and hence not part of the
savepoint state. By default, we try to map each entry of the savepoint back to
the new program.
+在上面的示例中，print sink 是无状态的，因此不是 Savepoint 状态的一部分。默认情况下，我们尝试将 Savepoint
的每个条目映射回新程序。
-## Operations
+## 算子
-You can use the [command line client]({{ site.baseurl
}}/ops/cli.html#savepoints) to *trigger savepoints*, *cancel a job with a
savepoint*, *resume from savepoints*, and *dispose savepoints*.
+你可以使用[命令行客户端]({{site.baseurl}}/zh/ops/cli.html#Savepoint)来*触发 Savepoint
*，*取消具有 Savepoint *的作业，*从 Savepoint *恢复，以及*部署 Savepoint *。
-With Flink >= 1.2.0 it is also possible to *resume from savepoints* using the
webui.
+使用 Flink >= 1.2.0，还可以使用 webui *从 Savepoint 恢复*。
-### Triggering Savepoints
+### 触发 Savepoint
-When triggering a savepoint, a new savepoint directory is created where the
data as well as the meta data will be stored. The location of this directory
can be controlled by [configuring a default target directory](#configuration)
or by specifying a custom target directory with the trigger commands (see the
[`:targetDirectory` argument](#trigger-a-savepoint)).
+当触发 Savepoint 时，将创建一个新的 Savepoint
目录，其中存储数据和元数据。可以通过[配置默认目标目录](#configuration)或使用触发器命令指定自定义目标目录(参见[`:targetDirectory
`参数](#trigger-a-savepoint)来控制该目录的位置。
-Attention: The target directory has to be a location
accessible by both the JobManager(s) and TaskManager(s) e.g. a location on a
distributed file-system.
+注意:目标目录必须是 JobManager(s) 和 TaskManager(s)
都可以访问的位置，例如分布式文件系统上的位置。
-For example with a `FsStateBackend` or `RocksDBStateBackend`:
+例如，使用 `FsStateBackend` 或 `RocksDBStateBackend` ：
{% highlight shell %}
-# Savepoint target directory
-/savepoints/
+# Savepoint 目标目录
+/Savepoint/
-# Savepoint directory
-/savepoints/savepoint-:shortjobid-:savepointid/
+# Savepoint 目录
+/Savepoint/savepoint-:shortjobid-:savepointid/
-# Savepoint file contains the checkpoint meta data
-/savepoints/savepoint-:shortjobid-:savepointid/_metadata
+# Savepoint 文件包含 Checkpoint元数据
+/Savepoint/savepoint-:shortjobid-:savepointid/_metadata
-# Savepoint state
-/savepoints/savepoint-:shortjobid-:savepointid/...
+# Savepoint 状态
+/Savepoint/savepoint-:shortjobid-:savepointid/...
{% endhighlight %}
- Note:
-Although it looks as if the savepoints may be moved, it is currently not
possible due to absolute paths in the _metadata file.
-Please follow https://issues.apache.org/jira/browse/FLINK-5778;>FLINK-5778 for
progress on lifting this restriction.
+ 注意:
+虽然看起来好像可以移动 Savepoint ，但由于 _metadata 文件中的绝对路径，目前无法进行保存。
+请按照https://issues.apache.org/jira/browse/FLINK-5778;> FLINK-5778
了解取消此限制的进度。
-
-Note that if you use the `MemoryStateBackend`, metadata *and* savepoint state
will be stored in the `_metadata` file. Since it is self-contained, you may
move the file and restore from any location.
+请注意，如果使用 `MemoryStateBackend`，则元数据*和* Savepoint 状态将存储在`_metadata`文件中。
由于它是自包含的，你可以移动文件并从任何位置恢复。
- Attention: It is discouraged to move or delete the last
savepoint of a running job, because this might interfere with failure-recovery.
Savepoints have side-effects on exactly-once sinks, therefore
- to ensure exactly-once semantics, if there is no checkpoint after the last
savepoint, the savepoint will be used for recovery.
+ 注意: 不建议移动或删除正在运行作业的最后一个 Savepoint
，因为这可能会干扰故障恢复。因此，Savepoint 对完全一次的接收器有副作用，为了确保精确的一次语义，如果在最后一个 Savepoint 之后没有
Checkpoint ，那么将使用 Savepoint 进行恢复。
- Trigger a Savepoint
+
+ 触发 Savepoint
{% highlight shell %}
$ bin/flink savepoint :jobId [:targetDirectory]
{% endhighlight %}
-This will trigger a savepoint for the job with ID `:jobId`, and returns the
path of the created savepoint. You need this path to restore and dispose
savepoints.
+这将触发ID为`：jobId`的作业的Savepoint，并返回创建的 Savepoint 的路径。 你需要此路径来还原和部署 Savepoint 。
- Trigger a Savepoint with YARN
+ 使用 YARN 触发 Savepoint
{% highlight shell %}
$ bin/flink savepoint :jobId [:targetDirectory] -yid :yarnAppId
{% endhighlight %}
-This will trigger a savepoint for the job with ID `:jobId` and YARN
application ID `:yarnAppId`, and returns the path of the created savepoint.
+这将触发 ID 为`：jobId` 和 YARN 应用程序 ID `：yarnAppId`的作业的 Savepoint，并返回创建的 Savepoint
的路径。
- Cancel Job with Savepoint
+ 使用 Savepoint 取消作业
{% highlight shell %}
$ bin/flink cancel -s [:targetDirectory] :jobId
{% endhighlight %}
-This will atomically trigger a savepoint for the job with ID `:jobid` and
cancel the job. Furthermore, you can specify a target file system directory to
store the savepoint in. The directory
[GitHub] [flink] klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh] Translate Savepoints page into Chinese
klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh]
Translate Savepoints page into Chinese
URL: https://github.com/apache/flink/pull/8300#discussion_r281070548
##
File path: docs/ops/state/savepoints.zh.md
##
@@ -78,160 +68,158 @@ source-id | State of StatefulSource
mapper-id | State of StatefulMapper
{% endhighlight %}
-In the above example, the print sink is stateless and hence not part of the
savepoint state. By default, we try to map each entry of the savepoint back to
the new program.
+在上面的示例中，print sink 是无状态的，因此不是 Savepoint 状态的一部分。默认情况下，我们尝试将 Savepoint
的每个条目映射回新程序。
-## Operations
+## 算子
-You can use the [command line client]({{ site.baseurl
}}/ops/cli.html#savepoints) to *trigger savepoints*, *cancel a job with a
savepoint*, *resume from savepoints*, and *dispose savepoints*.
+你可以使用[命令行客户端]({{site.baseurl}}/zh/ops/cli.html#Savepoint)来*触发 Savepoint
*，*取消具有 Savepoint *的作业，*从 Savepoint *恢复，以及*部署 Savepoint *。
-With Flink >= 1.2.0 it is also possible to *resume from savepoints* using the
webui.
+使用 Flink >= 1.2.0，还可以使用 webui *从 Savepoint 恢复*。
-### Triggering Savepoints
+### 触发 Savepoint
-When triggering a savepoint, a new savepoint directory is created where the
data as well as the meta data will be stored. The location of this directory
can be controlled by [configuring a default target directory](#configuration)
or by specifying a custom target directory with the trigger commands (see the
[`:targetDirectory` argument](#trigger-a-savepoint)).
+当触发 Savepoint 时，将创建一个新的 Savepoint
目录，其中存储数据和元数据。可以通过[配置默认目标目录](#configuration)或使用触发器命令指定自定义目标目录(参见[`:targetDirectory
`参数](#trigger-a-savepoint)来控制该目录的位置。
-Attention: The target directory has to be a location
accessible by both the JobManager(s) and TaskManager(s) e.g. a location on a
distributed file-system.
+注意:目标目录必须是 JobManager(s) 和 TaskManager(s)
都可以访问的位置，例如分布式文件系统上的位置。
-For example with a `FsStateBackend` or `RocksDBStateBackend`:
+例如，使用 `FsStateBackend` 或 `RocksDBStateBackend` ：
{% highlight shell %}
-# Savepoint target directory
-/savepoints/
+# Savepoint 目标目录
+/Savepoint/
-# Savepoint directory
-/savepoints/savepoint-:shortjobid-:savepointid/
+# Savepoint 目录
+/Savepoint/savepoint-:shortjobid-:savepointid/
-# Savepoint file contains the checkpoint meta data
-/savepoints/savepoint-:shortjobid-:savepointid/_metadata
+# Savepoint 文件包含 Checkpoint元数据
+/Savepoint/savepoint-:shortjobid-:savepointid/_metadata
-# Savepoint state
-/savepoints/savepoint-:shortjobid-:savepointid/...
+# Savepoint 状态
+/Savepoint/savepoint-:shortjobid-:savepointid/...
{% endhighlight %}
- Note:
-Although it looks as if the savepoints may be moved, it is currently not
possible due to absolute paths in the _metadata file.
-Please follow https://issues.apache.org/jira/browse/FLINK-5778;>FLINK-5778 for
progress on lifting this restriction.
+ 注意:
+虽然看起来好像可以移动 Savepoint ，但由于 _metadata 文件中的绝对路径，目前无法进行保存。
+请按照https://issues.apache.org/jira/browse/FLINK-5778;> FLINK-5778
了解取消此限制的进度。
-
-Note that if you use the `MemoryStateBackend`, metadata *and* savepoint state
will be stored in the `_metadata` file. Since it is self-contained, you may
move the file and restore from any location.
+请注意，如果使用 `MemoryStateBackend`，则元数据*和* Savepoint 状态将存储在`_metadata`文件中。
由于它是自包含的，你可以移动文件并从任何位置恢复。
- Attention: It is discouraged to move or delete the last
savepoint of a running job, because this might interfere with failure-recovery.
Savepoints have side-effects on exactly-once sinks, therefore
- to ensure exactly-once semantics, if there is no checkpoint after the last
savepoint, the savepoint will be used for recovery.
+ 注意: 不建议移动或删除正在运行作业的最后一个 Savepoint
，因为这可能会干扰故障恢复。因此，Savepoint 对完全一次的接收器有副作用，为了确保精确的一次语义，如果在最后一个 Savepoint 之后没有
Checkpoint ，那么将使用 Savepoint 进行恢复。
- Trigger a Savepoint
+
+ 触发 Savepoint
{% highlight shell %}
$ bin/flink savepoint :jobId [:targetDirectory]
{% endhighlight %}
-This will trigger a savepoint for the job with ID `:jobId`, and returns the
path of the created savepoint. You need this path to restore and dispose
savepoints.
+这将触发ID为`：jobId`的作业的Savepoint，并返回创建的 Savepoint 的路径。 你需要此路径来还原和部署 Savepoint 。
- Trigger a Savepoint with YARN
+ 使用 YARN 触发 Savepoint
{% highlight shell %}
$ bin/flink savepoint :jobId [:targetDirectory] -yid :yarnAppId
{% endhighlight %}
-This will trigger a savepoint for the job with ID `:jobId` and YARN
application ID `:yarnAppId`, and returns the path of the created savepoint.
+这将触发 ID 为`：jobId` 和 YARN 应用程序 ID `：yarnAppId`的作业的 Savepoint，并返回创建的 Savepoint
的路径。
- Cancel Job with Savepoint
+ 使用 Savepoint 取消作业
{% highlight shell %}
$ bin/flink cancel -s [:targetDirectory] :jobId
{% endhighlight %}
-This will atomically trigger a savepoint for the job with ID `:jobid` and
cancel the job. Furthermore, you can specify a target file system directory to
store the savepoint in. The directory
[GitHub] [flink] klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh] Translate Savepoints page into Chinese
klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh]
Translate Savepoints page into Chinese
URL: https://github.com/apache/flink/pull/8300#discussion_r281073725
##
File path: docs/ops/state/savepoints.zh.md
##
@@ -78,160 +68,158 @@ source-id | State of StatefulSource
mapper-id | State of StatefulMapper
{% endhighlight %}
-In the above example, the print sink is stateless and hence not part of the
savepoint state. By default, we try to map each entry of the savepoint back to
the new program.
+在上面的示例中，print sink 是无状态的，因此不是 Savepoint 状态的一部分。默认情况下，我们尝试将 Savepoint
的每个条目映射回新程序。
-## Operations
+## 算子
-You can use the [command line client]({{ site.baseurl
}}/ops/cli.html#savepoints) to *trigger savepoints*, *cancel a job with a
savepoint*, *resume from savepoints*, and *dispose savepoints*.
+你可以使用[命令行客户端]({{site.baseurl}}/zh/ops/cli.html#Savepoint)来*触发 Savepoint
*，*取消具有 Savepoint *的作业，*从 Savepoint *恢复，以及*部署 Savepoint *。
-With Flink >= 1.2.0 it is also possible to *resume from savepoints* using the
webui.
+使用 Flink >= 1.2.0，还可以使用 webui *从 Savepoint 恢复*。
-### Triggering Savepoints
+### 触发 Savepoint
-When triggering a savepoint, a new savepoint directory is created where the
data as well as the meta data will be stored. The location of this directory
can be controlled by [configuring a default target directory](#configuration)
or by specifying a custom target directory with the trigger commands (see the
[`:targetDirectory` argument](#trigger-a-savepoint)).
+当触发 Savepoint 时，将创建一个新的 Savepoint
目录，其中存储数据和元数据。可以通过[配置默认目标目录](#configuration)或使用触发器命令指定自定义目标目录(参见[`:targetDirectory
`参数](#trigger-a-savepoint)来控制该目录的位置。
-Attention: The target directory has to be a location
accessible by both the JobManager(s) and TaskManager(s) e.g. a location on a
distributed file-system.
+注意:目标目录必须是 JobManager(s) 和 TaskManager(s)
都可以访问的位置，例如分布式文件系统上的位置。
-For example with a `FsStateBackend` or `RocksDBStateBackend`:
+例如，使用 `FsStateBackend` 或 `RocksDBStateBackend` ：
{% highlight shell %}
-# Savepoint target directory
-/savepoints/
+# Savepoint 目标目录
+/Savepoint/
-# Savepoint directory
-/savepoints/savepoint-:shortjobid-:savepointid/
+# Savepoint 目录
+/Savepoint/savepoint-:shortjobid-:savepointid/
-# Savepoint file contains the checkpoint meta data
-/savepoints/savepoint-:shortjobid-:savepointid/_metadata
+# Savepoint 文件包含 Checkpoint元数据
+/Savepoint/savepoint-:shortjobid-:savepointid/_metadata
-# Savepoint state
-/savepoints/savepoint-:shortjobid-:savepointid/...
+# Savepoint 状态
+/Savepoint/savepoint-:shortjobid-:savepointid/...
{% endhighlight %}
- Note:
-Although it looks as if the savepoints may be moved, it is currently not
possible due to absolute paths in the _metadata file.
-Please follow https://issues.apache.org/jira/browse/FLINK-5778;>FLINK-5778 for
progress on lifting this restriction.
+ 注意:
+虽然看起来好像可以移动 Savepoint ，但由于 _metadata 文件中的绝对路径，目前无法进行保存。
+请按照https://issues.apache.org/jira/browse/FLINK-5778;> FLINK-5778
了解取消此限制的进度。
-
-Note that if you use the `MemoryStateBackend`, metadata *and* savepoint state
will be stored in the `_metadata` file. Since it is self-contained, you may
move the file and restore from any location.
+请注意，如果使用 `MemoryStateBackend`，则元数据*和* Savepoint 状态将存储在`_metadata`文件中。
由于它是自包含的，你可以移动文件并从任何位置恢复。
- Attention: It is discouraged to move or delete the last
savepoint of a running job, because this might interfere with failure-recovery.
Savepoints have side-effects on exactly-once sinks, therefore
- to ensure exactly-once semantics, if there is no checkpoint after the last
savepoint, the savepoint will be used for recovery.
+ 注意: 不建议移动或删除正在运行作业的最后一个 Savepoint
，因为这可能会干扰故障恢复。因此，Savepoint 对完全一次的接收器有副作用，为了确保精确的一次语义，如果在最后一个 Savepoint 之后没有
Checkpoint ，那么将使用 Savepoint 进行恢复。
- Trigger a Savepoint
+
+ 触发 Savepoint
{% highlight shell %}
$ bin/flink savepoint :jobId [:targetDirectory]
{% endhighlight %}
-This will trigger a savepoint for the job with ID `:jobId`, and returns the
path of the created savepoint. You need this path to restore and dispose
savepoints.
+这将触发ID为`：jobId`的作业的Savepoint，并返回创建的 Savepoint 的路径。 你需要此路径来还原和部署 Savepoint 。
- Trigger a Savepoint with YARN
+ 使用 YARN 触发 Savepoint
{% highlight shell %}
$ bin/flink savepoint :jobId [:targetDirectory] -yid :yarnAppId
{% endhighlight %}
-This will trigger a savepoint for the job with ID `:jobId` and YARN
application ID `:yarnAppId`, and returns the path of the created savepoint.
+这将触发 ID 为`：jobId` 和 YARN 应用程序 ID `：yarnAppId`的作业的 Savepoint，并返回创建的 Savepoint
的路径。
- Cancel Job with Savepoint
+ 使用 Savepoint 取消作业
{% highlight shell %}
$ bin/flink cancel -s [:targetDirectory] :jobId
{% endhighlight %}
-This will atomically trigger a savepoint for the job with ID `:jobid` and
cancel the job. Furthermore, you can specify a target file system directory to
store the savepoint in. The directory
[GitHub] [flink] klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh] Translate Savepoints page into Chinese
klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh]
Translate Savepoints page into Chinese
URL: https://github.com/apache/flink/pull/8300#discussion_r281074843
##
File path: docs/ops/state/savepoints.zh.md
##
@@ -78,160 +68,158 @@ source-id | State of StatefulSource
mapper-id | State of StatefulMapper
{% endhighlight %}
-In the above example, the print sink is stateless and hence not part of the
savepoint state. By default, we try to map each entry of the savepoint back to
the new program.
+在上面的示例中，print sink 是无状态的，因此不是 Savepoint 状态的一部分。默认情况下，我们尝试将 Savepoint
的每个条目映射回新程序。
-## Operations
+## 算子
-You can use the [command line client]({{ site.baseurl
}}/ops/cli.html#savepoints) to *trigger savepoints*, *cancel a job with a
savepoint*, *resume from savepoints*, and *dispose savepoints*.
+你可以使用[命令行客户端]({{site.baseurl}}/zh/ops/cli.html#Savepoint)来*触发 Savepoint
*，*取消具有 Savepoint *的作业，*从 Savepoint *恢复，以及*部署 Savepoint *。
-With Flink >= 1.2.0 it is also possible to *resume from savepoints* using the
webui.
+使用 Flink >= 1.2.0，还可以使用 webui *从 Savepoint 恢复*。
-### Triggering Savepoints
+### 触发 Savepoint
-When triggering a savepoint, a new savepoint directory is created where the
data as well as the meta data will be stored. The location of this directory
can be controlled by [configuring a default target directory](#configuration)
or by specifying a custom target directory with the trigger commands (see the
[`:targetDirectory` argument](#trigger-a-savepoint)).
+当触发 Savepoint 时，将创建一个新的 Savepoint
目录，其中存储数据和元数据。可以通过[配置默认目标目录](#configuration)或使用触发器命令指定自定义目标目录(参见[`:targetDirectory
`参数](#trigger-a-savepoint)来控制该目录的位置。
-Attention: The target directory has to be a location
accessible by both the JobManager(s) and TaskManager(s) e.g. a location on a
distributed file-system.
+注意:目标目录必须是 JobManager(s) 和 TaskManager(s)
都可以访问的位置，例如分布式文件系统上的位置。
-For example with a `FsStateBackend` or `RocksDBStateBackend`:
+例如，使用 `FsStateBackend` 或 `RocksDBStateBackend` ：
{% highlight shell %}
-# Savepoint target directory
-/savepoints/
+# Savepoint 目标目录
+/Savepoint/
-# Savepoint directory
-/savepoints/savepoint-:shortjobid-:savepointid/
+# Savepoint 目录
+/Savepoint/savepoint-:shortjobid-:savepointid/
-# Savepoint file contains the checkpoint meta data
-/savepoints/savepoint-:shortjobid-:savepointid/_metadata
+# Savepoint 文件包含 Checkpoint元数据
+/Savepoint/savepoint-:shortjobid-:savepointid/_metadata
-# Savepoint state
-/savepoints/savepoint-:shortjobid-:savepointid/...
+# Savepoint 状态
+/Savepoint/savepoint-:shortjobid-:savepointid/...
{% endhighlight %}
- Note:
-Although it looks as if the savepoints may be moved, it is currently not
possible due to absolute paths in the _metadata file.
-Please follow https://issues.apache.org/jira/browse/FLINK-5778;>FLINK-5778 for
progress on lifting this restriction.
+ 注意:
+虽然看起来好像可以移动 Savepoint ，但由于 _metadata 文件中的绝对路径，目前无法进行保存。
+请按照https://issues.apache.org/jira/browse/FLINK-5778;> FLINK-5778
了解取消此限制的进度。
-
-Note that if you use the `MemoryStateBackend`, metadata *and* savepoint state
will be stored in the `_metadata` file. Since it is self-contained, you may
move the file and restore from any location.
+请注意，如果使用 `MemoryStateBackend`，则元数据*和* Savepoint 状态将存储在`_metadata`文件中。
由于它是自包含的，你可以移动文件并从任何位置恢复。
- Attention: It is discouraged to move or delete the last
savepoint of a running job, because this might interfere with failure-recovery.
Savepoints have side-effects on exactly-once sinks, therefore
- to ensure exactly-once semantics, if there is no checkpoint after the last
savepoint, the savepoint will be used for recovery.
+ 注意: 不建议移动或删除正在运行作业的最后一个 Savepoint
，因为这可能会干扰故障恢复。因此，Savepoint 对完全一次的接收器有副作用，为了确保精确的一次语义，如果在最后一个 Savepoint 之后没有
Checkpoint ，那么将使用 Savepoint 进行恢复。
- Trigger a Savepoint
+
+ 触发 Savepoint
{% highlight shell %}
$ bin/flink savepoint :jobId [:targetDirectory]
{% endhighlight %}
-This will trigger a savepoint for the job with ID `:jobId`, and returns the
path of the created savepoint. You need this path to restore and dispose
savepoints.
+这将触发ID为`：jobId`的作业的Savepoint，并返回创建的 Savepoint 的路径。 你需要此路径来还原和部署 Savepoint 。
- Trigger a Savepoint with YARN
+ 使用 YARN 触发 Savepoint
{% highlight shell %}
$ bin/flink savepoint :jobId [:targetDirectory] -yid :yarnAppId
{% endhighlight %}
-This will trigger a savepoint for the job with ID `:jobId` and YARN
application ID `:yarnAppId`, and returns the path of the created savepoint.
+这将触发 ID 为`：jobId` 和 YARN 应用程序 ID `：yarnAppId`的作业的 Savepoint，并返回创建的 Savepoint
的路径。
- Cancel Job with Savepoint
+ 使用 Savepoint 取消作业
{% highlight shell %}
$ bin/flink cancel -s [:targetDirectory] :jobId
{% endhighlight %}
-This will atomically trigger a savepoint for the job with ID `:jobid` and
cancel the job. Furthermore, you can specify a target file system directory to
store the savepoint in. The directory
[GitHub] [flink] klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh] Translate Savepoints page into Chinese
klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh]
Translate Savepoints page into Chinese
URL: https://github.com/apache/flink/pull/8300#discussion_r281072845
##
File path: docs/ops/state/savepoints.zh.md
##
@@ -78,160 +68,158 @@ source-id | State of StatefulSource
mapper-id | State of StatefulMapper
{% endhighlight %}
-In the above example, the print sink is stateless and hence not part of the
savepoint state. By default, we try to map each entry of the savepoint back to
the new program.
+在上面的示例中，print sink 是无状态的，因此不是 Savepoint 状态的一部分。默认情况下，我们尝试将 Savepoint
的每个条目映射回新程序。
-## Operations
+## 算子
-You can use the [command line client]({{ site.baseurl
}}/ops/cli.html#savepoints) to *trigger savepoints*, *cancel a job with a
savepoint*, *resume from savepoints*, and *dispose savepoints*.
+你可以使用[命令行客户端]({{site.baseurl}}/zh/ops/cli.html#Savepoint)来*触发 Savepoint
*，*取消具有 Savepoint *的作业，*从 Savepoint *恢复，以及*部署 Savepoint *。
-With Flink >= 1.2.0 it is also possible to *resume from savepoints* using the
webui.
+使用 Flink >= 1.2.0，还可以使用 webui *从 Savepoint 恢复*。
-### Triggering Savepoints
+### 触发 Savepoint
-When triggering a savepoint, a new savepoint directory is created where the
data as well as the meta data will be stored. The location of this directory
can be controlled by [configuring a default target directory](#configuration)
or by specifying a custom target directory with the trigger commands (see the
[`:targetDirectory` argument](#trigger-a-savepoint)).
+当触发 Savepoint 时，将创建一个新的 Savepoint
目录，其中存储数据和元数据。可以通过[配置默认目标目录](#configuration)或使用触发器命令指定自定义目标目录(参见[`:targetDirectory
`参数](#trigger-a-savepoint)来控制该目录的位置。
-Attention: The target directory has to be a location
accessible by both the JobManager(s) and TaskManager(s) e.g. a location on a
distributed file-system.
+注意:目标目录必须是 JobManager(s) 和 TaskManager(s)
都可以访问的位置，例如分布式文件系统上的位置。
-For example with a `FsStateBackend` or `RocksDBStateBackend`:
+例如，使用 `FsStateBackend` 或 `RocksDBStateBackend` ：
{% highlight shell %}
-# Savepoint target directory
-/savepoints/
+# Savepoint 目标目录
+/Savepoint/
-# Savepoint directory
-/savepoints/savepoint-:shortjobid-:savepointid/
+# Savepoint 目录
+/Savepoint/savepoint-:shortjobid-:savepointid/
-# Savepoint file contains the checkpoint meta data
-/savepoints/savepoint-:shortjobid-:savepointid/_metadata
+# Savepoint 文件包含 Checkpoint元数据
+/Savepoint/savepoint-:shortjobid-:savepointid/_metadata
-# Savepoint state
-/savepoints/savepoint-:shortjobid-:savepointid/...
+# Savepoint 状态
+/Savepoint/savepoint-:shortjobid-:savepointid/...
{% endhighlight %}
- Note:
-Although it looks as if the savepoints may be moved, it is currently not
possible due to absolute paths in the _metadata file.
-Please follow https://issues.apache.org/jira/browse/FLINK-5778;>FLINK-5778 for
progress on lifting this restriction.
+ 注意:
+虽然看起来好像可以移动 Savepoint ，但由于 _metadata 文件中的绝对路径，目前无法进行保存。
+请按照https://issues.apache.org/jira/browse/FLINK-5778;> FLINK-5778
了解取消此限制的进度。
-
-Note that if you use the `MemoryStateBackend`, metadata *and* savepoint state
will be stored in the `_metadata` file. Since it is self-contained, you may
move the file and restore from any location.
+请注意，如果使用 `MemoryStateBackend`，则元数据*和* Savepoint 状态将存储在`_metadata`文件中。
由于它是自包含的，你可以移动文件并从任何位置恢复。
- Attention: It is discouraged to move or delete the last
savepoint of a running job, because this might interfere with failure-recovery.
Savepoints have side-effects on exactly-once sinks, therefore
- to ensure exactly-once semantics, if there is no checkpoint after the last
savepoint, the savepoint will be used for recovery.
+ 注意: 不建议移动或删除正在运行作业的最后一个 Savepoint
，因为这可能会干扰故障恢复。因此，Savepoint 对完全一次的接收器有副作用，为了确保精确的一次语义，如果在最后一个 Savepoint 之后没有
Checkpoint ，那么将使用 Savepoint 进行恢复。
- Trigger a Savepoint
+
+ 触发 Savepoint
{% highlight shell %}
$ bin/flink savepoint :jobId [:targetDirectory]
{% endhighlight %}
-This will trigger a savepoint for the job with ID `:jobId`, and returns the
path of the created savepoint. You need this path to restore and dispose
savepoints.
+这将触发ID为`：jobId`的作业的Savepoint，并返回创建的 Savepoint 的路径。 你需要此路径来还原和部署 Savepoint 。
- Trigger a Savepoint with YARN
+ 使用 YARN 触发 Savepoint
{% highlight shell %}
$ bin/flink savepoint :jobId [:targetDirectory] -yid :yarnAppId
{% endhighlight %}
-This will trigger a savepoint for the job with ID `:jobId` and YARN
application ID `:yarnAppId`, and returns the path of the created savepoint.
+这将触发 ID 为`：jobId` 和 YARN 应用程序 ID `：yarnAppId`的作业的 Savepoint，并返回创建的 Savepoint
的路径。
- Cancel Job with Savepoint
+ 使用 Savepoint 取消作业
{% highlight shell %}
$ bin/flink cancel -s [:targetDirectory] :jobId
{% endhighlight %}
-This will atomically trigger a savepoint for the job with ID `:jobid` and
cancel the job. Furthermore, you can specify a target file system directory to
store the savepoint in. The directory
[GitHub] [flink] klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh] Translate Savepoints page into Chinese
klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh]
Translate Savepoints page into Chinese
URL: https://github.com/apache/flink/pull/8300#discussion_r281071124
##
File path: docs/ops/state/savepoints.zh.md
##
@@ -78,160 +68,158 @@ source-id | State of StatefulSource
mapper-id | State of StatefulMapper
{% endhighlight %}
-In the above example, the print sink is stateless and hence not part of the
savepoint state. By default, we try to map each entry of the savepoint back to
the new program.
+在上面的示例中，print sink 是无状态的，因此不是 Savepoint 状态的一部分。默认情况下，我们尝试将 Savepoint
的每个条目映射回新程序。
-## Operations
+## 算子
-You can use the [command line client]({{ site.baseurl
}}/ops/cli.html#savepoints) to *trigger savepoints*, *cancel a job with a
savepoint*, *resume from savepoints*, and *dispose savepoints*.
+你可以使用[命令行客户端]({{site.baseurl}}/zh/ops/cli.html#Savepoint)来*触发 Savepoint
*，*取消具有 Savepoint *的作业，*从 Savepoint *恢复，以及*部署 Savepoint *。
-With Flink >= 1.2.0 it is also possible to *resume from savepoints* using the
webui.
+使用 Flink >= 1.2.0，还可以使用 webui *从 Savepoint 恢复*。
-### Triggering Savepoints
+### 触发 Savepoint
-When triggering a savepoint, a new savepoint directory is created where the
data as well as the meta data will be stored. The location of this directory
can be controlled by [configuring a default target directory](#configuration)
or by specifying a custom target directory with the trigger commands (see the
[`:targetDirectory` argument](#trigger-a-savepoint)).
+当触发 Savepoint 时，将创建一个新的 Savepoint
目录，其中存储数据和元数据。可以通过[配置默认目标目录](#configuration)或使用触发器命令指定自定义目标目录(参见[`:targetDirectory
`参数](#trigger-a-savepoint)来控制该目录的位置。
-Attention: The target directory has to be a location
accessible by both the JobManager(s) and TaskManager(s) e.g. a location on a
distributed file-system.
+注意:目标目录必须是 JobManager(s) 和 TaskManager(s)
都可以访问的位置，例如分布式文件系统上的位置。
-For example with a `FsStateBackend` or `RocksDBStateBackend`:
+例如，使用 `FsStateBackend` 或 `RocksDBStateBackend` ：
{% highlight shell %}
-# Savepoint target directory
-/savepoints/
+# Savepoint 目标目录
+/Savepoint/
-# Savepoint directory
-/savepoints/savepoint-:shortjobid-:savepointid/
+# Savepoint 目录
+/Savepoint/savepoint-:shortjobid-:savepointid/
-# Savepoint file contains the checkpoint meta data
-/savepoints/savepoint-:shortjobid-:savepointid/_metadata
+# Savepoint 文件包含 Checkpoint元数据
+/Savepoint/savepoint-:shortjobid-:savepointid/_metadata
-# Savepoint state
-/savepoints/savepoint-:shortjobid-:savepointid/...
+# Savepoint 状态
+/Savepoint/savepoint-:shortjobid-:savepointid/...
{% endhighlight %}
- Note:
-Although it looks as if the savepoints may be moved, it is currently not
possible due to absolute paths in the _metadata file.
-Please follow https://issues.apache.org/jira/browse/FLINK-5778;>FLINK-5778 for
progress on lifting this restriction.
+ 注意:
+虽然看起来好像可以移动 Savepoint ，但由于 _metadata 文件中的绝对路径，目前无法进行保存。
+请按照https://issues.apache.org/jira/browse/FLINK-5778;> FLINK-5778
了解取消此限制的进度。
-
-Note that if you use the `MemoryStateBackend`, metadata *and* savepoint state
will be stored in the `_metadata` file. Since it is self-contained, you may
move the file and restore from any location.
+请注意，如果使用 `MemoryStateBackend`，则元数据*和* Savepoint 状态将存储在`_metadata`文件中。
由于它是自包含的，你可以移动文件并从任何位置恢复。
- Attention: It is discouraged to move or delete the last
savepoint of a running job, because this might interfere with failure-recovery.
Savepoints have side-effects on exactly-once sinks, therefore
- to ensure exactly-once semantics, if there is no checkpoint after the last
savepoint, the savepoint will be used for recovery.
+ 注意: 不建议移动或删除正在运行作业的最后一个 Savepoint
，因为这可能会干扰故障恢复。因此，Savepoint 对完全一次的接收器有副作用，为了确保精确的一次语义，如果在最后一个 Savepoint 之后没有
Checkpoint ，那么将使用 Savepoint 进行恢复。
- Trigger a Savepoint
+
+ 触发 Savepoint
{% highlight shell %}
$ bin/flink savepoint :jobId [:targetDirectory]
{% endhighlight %}
-This will trigger a savepoint for the job with ID `:jobId`, and returns the
path of the created savepoint. You need this path to restore and dispose
savepoints.
+这将触发ID为`：jobId`的作业的Savepoint，并返回创建的 Savepoint 的路径。 你需要此路径来还原和部署 Savepoint 。
- Trigger a Savepoint with YARN
+ 使用 YARN 触发 Savepoint
{% highlight shell %}
$ bin/flink savepoint :jobId [:targetDirectory] -yid :yarnAppId
{% endhighlight %}
-This will trigger a savepoint for the job with ID `:jobId` and YARN
application ID `:yarnAppId`, and returns the path of the created savepoint.
+这将触发 ID 为`：jobId` 和 YARN 应用程序 ID `：yarnAppId`的作业的 Savepoint，并返回创建的 Savepoint
的路径。
- Cancel Job with Savepoint
+ 使用 Savepoint 取消作业
{% highlight shell %}
$ bin/flink cancel -s [:targetDirectory] :jobId
{% endhighlight %}
-This will atomically trigger a savepoint for the job with ID `:jobid` and
cancel the job. Furthermore, you can specify a target file system directory to
store the savepoint in. The directory
[GitHub] [flink] klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh] Translate Savepoints page into Chinese
klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh]
Translate Savepoints page into Chinese
URL: https://github.com/apache/flink/pull/8300#discussion_r281075048
##
File path: docs/ops/state/savepoints.zh.md
##
@@ -78,160 +68,158 @@ source-id | State of StatefulSource
mapper-id | State of StatefulMapper
{% endhighlight %}
-In the above example, the print sink is stateless and hence not part of the
savepoint state. By default, we try to map each entry of the savepoint back to
the new program.
+在上面的示例中，print sink 是无状态的，因此不是 Savepoint 状态的一部分。默认情况下，我们尝试将 Savepoint
的每个条目映射回新程序。
-## Operations
+## 算子
-You can use the [command line client]({{ site.baseurl
}}/ops/cli.html#savepoints) to *trigger savepoints*, *cancel a job with a
savepoint*, *resume from savepoints*, and *dispose savepoints*.
+你可以使用[命令行客户端]({{site.baseurl}}/zh/ops/cli.html#Savepoint)来*触发 Savepoint
*，*取消具有 Savepoint *的作业，*从 Savepoint *恢复，以及*部署 Savepoint *。
-With Flink >= 1.2.0 it is also possible to *resume from savepoints* using the
webui.
+使用 Flink >= 1.2.0，还可以使用 webui *从 Savepoint 恢复*。
-### Triggering Savepoints
+### 触发 Savepoint
-When triggering a savepoint, a new savepoint directory is created where the
data as well as the meta data will be stored. The location of this directory
can be controlled by [configuring a default target directory](#configuration)
or by specifying a custom target directory with the trigger commands (see the
[`:targetDirectory` argument](#trigger-a-savepoint)).
+当触发 Savepoint 时，将创建一个新的 Savepoint
目录，其中存储数据和元数据。可以通过[配置默认目标目录](#configuration)或使用触发器命令指定自定义目标目录(参见[`:targetDirectory
`参数](#trigger-a-savepoint)来控制该目录的位置。
-Attention: The target directory has to be a location
accessible by both the JobManager(s) and TaskManager(s) e.g. a location on a
distributed file-system.
+注意:目标目录必须是 JobManager(s) 和 TaskManager(s)
都可以访问的位置，例如分布式文件系统上的位置。
-For example with a `FsStateBackend` or `RocksDBStateBackend`:
+例如，使用 `FsStateBackend` 或 `RocksDBStateBackend` ：
{% highlight shell %}
-# Savepoint target directory
-/savepoints/
+# Savepoint 目标目录
+/Savepoint/
-# Savepoint directory
-/savepoints/savepoint-:shortjobid-:savepointid/
+# Savepoint 目录
+/Savepoint/savepoint-:shortjobid-:savepointid/
-# Savepoint file contains the checkpoint meta data
-/savepoints/savepoint-:shortjobid-:savepointid/_metadata
+# Savepoint 文件包含 Checkpoint元数据
+/Savepoint/savepoint-:shortjobid-:savepointid/_metadata
-# Savepoint state
-/savepoints/savepoint-:shortjobid-:savepointid/...
+# Savepoint 状态
+/Savepoint/savepoint-:shortjobid-:savepointid/...
{% endhighlight %}
- Note:
-Although it looks as if the savepoints may be moved, it is currently not
possible due to absolute paths in the _metadata file.
-Please follow https://issues.apache.org/jira/browse/FLINK-5778;>FLINK-5778 for
progress on lifting this restriction.
+ 注意:
+虽然看起来好像可以移动 Savepoint ，但由于 _metadata 文件中的绝对路径，目前无法进行保存。
+请按照https://issues.apache.org/jira/browse/FLINK-5778;> FLINK-5778
了解取消此限制的进度。
-
-Note that if you use the `MemoryStateBackend`, metadata *and* savepoint state
will be stored in the `_metadata` file. Since it is self-contained, you may
move the file and restore from any location.
+请注意，如果使用 `MemoryStateBackend`，则元数据*和* Savepoint 状态将存储在`_metadata`文件中。
由于它是自包含的，你可以移动文件并从任何位置恢复。
- Attention: It is discouraged to move or delete the last
savepoint of a running job, because this might interfere with failure-recovery.
Savepoints have side-effects on exactly-once sinks, therefore
- to ensure exactly-once semantics, if there is no checkpoint after the last
savepoint, the savepoint will be used for recovery.
+ 注意: 不建议移动或删除正在运行作业的最后一个 Savepoint
，因为这可能会干扰故障恢复。因此，Savepoint 对完全一次的接收器有副作用，为了确保精确的一次语义，如果在最后一个 Savepoint 之后没有
Checkpoint ，那么将使用 Savepoint 进行恢复。
- Trigger a Savepoint
+
+ 触发 Savepoint
{% highlight shell %}
$ bin/flink savepoint :jobId [:targetDirectory]
{% endhighlight %}
-This will trigger a savepoint for the job with ID `:jobId`, and returns the
path of the created savepoint. You need this path to restore and dispose
savepoints.
+这将触发ID为`：jobId`的作业的Savepoint，并返回创建的 Savepoint 的路径。 你需要此路径来还原和部署 Savepoint 。
- Trigger a Savepoint with YARN
+ 使用 YARN 触发 Savepoint
{% highlight shell %}
$ bin/flink savepoint :jobId [:targetDirectory] -yid :yarnAppId
{% endhighlight %}
-This will trigger a savepoint for the job with ID `:jobId` and YARN
application ID `:yarnAppId`, and returns the path of the created savepoint.
+这将触发 ID 为`：jobId` 和 YARN 应用程序 ID `：yarnAppId`的作业的 Savepoint，并返回创建的 Savepoint
的路径。
- Cancel Job with Savepoint
+ 使用 Savepoint 取消作业
{% highlight shell %}
$ bin/flink cancel -s [:targetDirectory] :jobId
{% endhighlight %}
-This will atomically trigger a savepoint for the job with ID `:jobid` and
cancel the job. Furthermore, you can specify a target file system directory to
store the savepoint in. The directory
[GitHub] [flink] klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh] Translate Savepoints page into Chinese
klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh]
Translate Savepoints page into Chinese
URL: https://github.com/apache/flink/pull/8300#discussion_r281071746
##
File path: docs/ops/state/savepoints.zh.md
##
@@ -78,160 +68,158 @@ source-id | State of StatefulSource
mapper-id | State of StatefulMapper
{% endhighlight %}
-In the above example, the print sink is stateless and hence not part of the
savepoint state. By default, we try to map each entry of the savepoint back to
the new program.
+在上面的示例中，print sink 是无状态的，因此不是 Savepoint 状态的一部分。默认情况下，我们尝试将 Savepoint
的每个条目映射回新程序。
-## Operations
+## 算子
-You can use the [command line client]({{ site.baseurl
}}/ops/cli.html#savepoints) to *trigger savepoints*, *cancel a job with a
savepoint*, *resume from savepoints*, and *dispose savepoints*.
+你可以使用[命令行客户端]({{site.baseurl}}/zh/ops/cli.html#Savepoint)来*触发 Savepoint
*，*取消具有 Savepoint *的作业，*从 Savepoint *恢复，以及*部署 Savepoint *。
-With Flink >= 1.2.0 it is also possible to *resume from savepoints* using the
webui.
+使用 Flink >= 1.2.0，还可以使用 webui *从 Savepoint 恢复*。
-### Triggering Savepoints
+### 触发 Savepoint
-When triggering a savepoint, a new savepoint directory is created where the
data as well as the meta data will be stored. The location of this directory
can be controlled by [configuring a default target directory](#configuration)
or by specifying a custom target directory with the trigger commands (see the
[`:targetDirectory` argument](#trigger-a-savepoint)).
+当触发 Savepoint 时，将创建一个新的 Savepoint
目录，其中存储数据和元数据。可以通过[配置默认目标目录](#configuration)或使用触发器命令指定自定义目标目录(参见[`:targetDirectory
`参数](#trigger-a-savepoint)来控制该目录的位置。
-Attention: The target directory has to be a location
accessible by both the JobManager(s) and TaskManager(s) e.g. a location on a
distributed file-system.
+注意:目标目录必须是 JobManager(s) 和 TaskManager(s)
都可以访问的位置，例如分布式文件系统上的位置。
-For example with a `FsStateBackend` or `RocksDBStateBackend`:
+例如，使用 `FsStateBackend` 或 `RocksDBStateBackend` ：
{% highlight shell %}
-# Savepoint target directory
-/savepoints/
+# Savepoint 目标目录
+/Savepoint/
-# Savepoint directory
-/savepoints/savepoint-:shortjobid-:savepointid/
+# Savepoint 目录
+/Savepoint/savepoint-:shortjobid-:savepointid/
-# Savepoint file contains the checkpoint meta data
-/savepoints/savepoint-:shortjobid-:savepointid/_metadata
+# Savepoint 文件包含 Checkpoint元数据
+/Savepoint/savepoint-:shortjobid-:savepointid/_metadata
-# Savepoint state
-/savepoints/savepoint-:shortjobid-:savepointid/...
+# Savepoint 状态
+/Savepoint/savepoint-:shortjobid-:savepointid/...
{% endhighlight %}
- Note:
-Although it looks as if the savepoints may be moved, it is currently not
possible due to absolute paths in the _metadata file.
-Please follow https://issues.apache.org/jira/browse/FLINK-5778;>FLINK-5778 for
progress on lifting this restriction.
+ 注意:
+虽然看起来好像可以移动 Savepoint ，但由于 _metadata 文件中的绝对路径，目前无法进行保存。
+请按照https://issues.apache.org/jira/browse/FLINK-5778;> FLINK-5778
了解取消此限制的进度。
-
-Note that if you use the `MemoryStateBackend`, metadata *and* savepoint state
will be stored in the `_metadata` file. Since it is self-contained, you may
move the file and restore from any location.
+请注意，如果使用 `MemoryStateBackend`，则元数据*和* Savepoint 状态将存储在`_metadata`文件中。
由于它是自包含的，你可以移动文件并从任何位置恢复。
- Attention: It is discouraged to move or delete the last
savepoint of a running job, because this might interfere with failure-recovery.
Savepoints have side-effects on exactly-once sinks, therefore
- to ensure exactly-once semantics, if there is no checkpoint after the last
savepoint, the savepoint will be used for recovery.
+ 注意: 不建议移动或删除正在运行作业的最后一个 Savepoint
，因为这可能会干扰故障恢复。因此，Savepoint 对完全一次的接收器有副作用，为了确保精确的一次语义，如果在最后一个 Savepoint 之后没有
Checkpoint ，那么将使用 Savepoint 进行恢复。
- Trigger a Savepoint
+
+ 触发 Savepoint
{% highlight shell %}
$ bin/flink savepoint :jobId [:targetDirectory]
{% endhighlight %}
-This will trigger a savepoint for the job with ID `:jobId`, and returns the
path of the created savepoint. You need this path to restore and dispose
savepoints.
+这将触发ID为`：jobId`的作业的Savepoint，并返回创建的 Savepoint 的路径。 你需要此路径来还原和部署 Savepoint 。
- Trigger a Savepoint with YARN
+ 使用 YARN 触发 Savepoint
{% highlight shell %}
$ bin/flink savepoint :jobId [:targetDirectory] -yid :yarnAppId
{% endhighlight %}
-This will trigger a savepoint for the job with ID `:jobId` and YARN
application ID `:yarnAppId`, and returns the path of the created savepoint.
+这将触发 ID 为`：jobId` 和 YARN 应用程序 ID `：yarnAppId`的作业的 Savepoint，并返回创建的 Savepoint
的路径。
- Cancel Job with Savepoint
+ 使用 Savepoint 取消作业
{% highlight shell %}
$ bin/flink cancel -s [:targetDirectory] :jobId
{% endhighlight %}
-This will atomically trigger a savepoint for the job with ID `:jobid` and
cancel the job. Furthermore, you can specify a target file system directory to
store the savepoint in. The directory
[GitHub] [flink] klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh] Translate Savepoints page into Chinese
klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh]
Translate Savepoints page into Chinese
URL: https://github.com/apache/flink/pull/8300#discussion_r281071467
##
File path: docs/ops/state/savepoints.zh.md
##
@@ -78,160 +68,158 @@ source-id | State of StatefulSource
mapper-id | State of StatefulMapper
{% endhighlight %}
-In the above example, the print sink is stateless and hence not part of the
savepoint state. By default, we try to map each entry of the savepoint back to
the new program.
+在上面的示例中，print sink 是无状态的，因此不是 Savepoint 状态的一部分。默认情况下，我们尝试将 Savepoint
的每个条目映射回新程序。
-## Operations
+## 算子
-You can use the [command line client]({{ site.baseurl
}}/ops/cli.html#savepoints) to *trigger savepoints*, *cancel a job with a
savepoint*, *resume from savepoints*, and *dispose savepoints*.
+你可以使用[命令行客户端]({{site.baseurl}}/zh/ops/cli.html#Savepoint)来*触发 Savepoint
*，*取消具有 Savepoint *的作业，*从 Savepoint *恢复，以及*部署 Savepoint *。
-With Flink >= 1.2.0 it is also possible to *resume from savepoints* using the
webui.
+使用 Flink >= 1.2.0，还可以使用 webui *从 Savepoint 恢复*。
-### Triggering Savepoints
+### 触发 Savepoint
-When triggering a savepoint, a new savepoint directory is created where the
data as well as the meta data will be stored. The location of this directory
can be controlled by [configuring a default target directory](#configuration)
or by specifying a custom target directory with the trigger commands (see the
[`:targetDirectory` argument](#trigger-a-savepoint)).
+当触发 Savepoint 时，将创建一个新的 Savepoint
目录，其中存储数据和元数据。可以通过[配置默认目标目录](#configuration)或使用触发器命令指定自定义目标目录(参见[`:targetDirectory
`参数](#trigger-a-savepoint)来控制该目录的位置。
-Attention: The target directory has to be a location
accessible by both the JobManager(s) and TaskManager(s) e.g. a location on a
distributed file-system.
+注意:目标目录必须是 JobManager(s) 和 TaskManager(s)
都可以访问的位置，例如分布式文件系统上的位置。
-For example with a `FsStateBackend` or `RocksDBStateBackend`:
+例如，使用 `FsStateBackend` 或 `RocksDBStateBackend` ：
{% highlight shell %}
-# Savepoint target directory
-/savepoints/
+# Savepoint 目标目录
+/Savepoint/
-# Savepoint directory
-/savepoints/savepoint-:shortjobid-:savepointid/
+# Savepoint 目录
+/Savepoint/savepoint-:shortjobid-:savepointid/
-# Savepoint file contains the checkpoint meta data
-/savepoints/savepoint-:shortjobid-:savepointid/_metadata
+# Savepoint 文件包含 Checkpoint元数据
+/Savepoint/savepoint-:shortjobid-:savepointid/_metadata
-# Savepoint state
-/savepoints/savepoint-:shortjobid-:savepointid/...
+# Savepoint 状态
+/Savepoint/savepoint-:shortjobid-:savepointid/...
{% endhighlight %}
- Note:
-Although it looks as if the savepoints may be moved, it is currently not
possible due to absolute paths in the _metadata file.
-Please follow https://issues.apache.org/jira/browse/FLINK-5778;>FLINK-5778 for
progress on lifting this restriction.
+ 注意:
+虽然看起来好像可以移动 Savepoint ，但由于 _metadata 文件中的绝对路径，目前无法进行保存。
+请按照https://issues.apache.org/jira/browse/FLINK-5778;> FLINK-5778
了解取消此限制的进度。
-
-Note that if you use the `MemoryStateBackend`, metadata *and* savepoint state
will be stored in the `_metadata` file. Since it is self-contained, you may
move the file and restore from any location.
+请注意，如果使用 `MemoryStateBackend`，则元数据*和* Savepoint 状态将存储在`_metadata`文件中。
由于它是自包含的，你可以移动文件并从任何位置恢复。
- Attention: It is discouraged to move or delete the last
savepoint of a running job, because this might interfere with failure-recovery.
Savepoints have side-effects on exactly-once sinks, therefore
- to ensure exactly-once semantics, if there is no checkpoint after the last
savepoint, the savepoint will be used for recovery.
+ 注意: 不建议移动或删除正在运行作业的最后一个 Savepoint
，因为这可能会干扰故障恢复。因此，Savepoint 对完全一次的接收器有副作用，为了确保精确的一次语义，如果在最后一个 Savepoint 之后没有
Checkpoint ，那么将使用 Savepoint 进行恢复。
- Trigger a Savepoint
+
+ 触发 Savepoint
{% highlight shell %}
$ bin/flink savepoint :jobId [:targetDirectory]
{% endhighlight %}
-This will trigger a savepoint for the job with ID `:jobId`, and returns the
path of the created savepoint. You need this path to restore and dispose
savepoints.
+这将触发ID为`：jobId`的作业的Savepoint，并返回创建的 Savepoint 的路径。 你需要此路径来还原和部署 Savepoint 。
- Trigger a Savepoint with YARN
+ 使用 YARN 触发 Savepoint
{% highlight shell %}
$ bin/flink savepoint :jobId [:targetDirectory] -yid :yarnAppId
{% endhighlight %}
-This will trigger a savepoint for the job with ID `:jobId` and YARN
application ID `:yarnAppId`, and returns the path of the created savepoint.
+这将触发 ID 为`：jobId` 和 YARN 应用程序 ID `：yarnAppId`的作业的 Savepoint，并返回创建的 Savepoint
的路径。
- Cancel Job with Savepoint
+ 使用 Savepoint 取消作业
{% highlight shell %}
$ bin/flink cancel -s [:targetDirectory] :jobId
{% endhighlight %}
-This will atomically trigger a savepoint for the job with ID `:jobid` and
cancel the job. Furthermore, you can specify a target file system directory to
store the savepoint in. The directory
[GitHub] [flink] klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh] Translate Savepoints page into Chinese
klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh]
Translate Savepoints page into Chinese
URL: https://github.com/apache/flink/pull/8300#discussion_r281072801
##
File path: docs/ops/state/savepoints.zh.md
##
@@ -78,160 +68,158 @@ source-id | State of StatefulSource
mapper-id | State of StatefulMapper
{% endhighlight %}
-In the above example, the print sink is stateless and hence not part of the
savepoint state. By default, we try to map each entry of the savepoint back to
the new program.
+在上面的示例中，print sink 是无状态的，因此不是 Savepoint 状态的一部分。默认情况下，我们尝试将 Savepoint
的每个条目映射回新程序。
-## Operations
+## 算子
-You can use the [command line client]({{ site.baseurl
}}/ops/cli.html#savepoints) to *trigger savepoints*, *cancel a job with a
savepoint*, *resume from savepoints*, and *dispose savepoints*.
+你可以使用[命令行客户端]({{site.baseurl}}/zh/ops/cli.html#Savepoint)来*触发 Savepoint
*，*取消具有 Savepoint *的作业，*从 Savepoint *恢复，以及*部署 Savepoint *。
-With Flink >= 1.2.0 it is also possible to *resume from savepoints* using the
webui.
+使用 Flink >= 1.2.0，还可以使用 webui *从 Savepoint 恢复*。
-### Triggering Savepoints
+### 触发 Savepoint
-When triggering a savepoint, a new savepoint directory is created where the
data as well as the meta data will be stored. The location of this directory
can be controlled by [configuring a default target directory](#configuration)
or by specifying a custom target directory with the trigger commands (see the
[`:targetDirectory` argument](#trigger-a-savepoint)).
+当触发 Savepoint 时，将创建一个新的 Savepoint
目录，其中存储数据和元数据。可以通过[配置默认目标目录](#configuration)或使用触发器命令指定自定义目标目录(参见[`:targetDirectory
`参数](#trigger-a-savepoint)来控制该目录的位置。
-Attention: The target directory has to be a location
accessible by both the JobManager(s) and TaskManager(s) e.g. a location on a
distributed file-system.
+注意:目标目录必须是 JobManager(s) 和 TaskManager(s)
都可以访问的位置，例如分布式文件系统上的位置。
-For example with a `FsStateBackend` or `RocksDBStateBackend`:
+例如，使用 `FsStateBackend` 或 `RocksDBStateBackend` ：
{% highlight shell %}
-# Savepoint target directory
-/savepoints/
+# Savepoint 目标目录
+/Savepoint/
-# Savepoint directory
-/savepoints/savepoint-:shortjobid-:savepointid/
+# Savepoint 目录
+/Savepoint/savepoint-:shortjobid-:savepointid/
-# Savepoint file contains the checkpoint meta data
-/savepoints/savepoint-:shortjobid-:savepointid/_metadata
+# Savepoint 文件包含 Checkpoint元数据
+/Savepoint/savepoint-:shortjobid-:savepointid/_metadata
-# Savepoint state
-/savepoints/savepoint-:shortjobid-:savepointid/...
+# Savepoint 状态
+/Savepoint/savepoint-:shortjobid-:savepointid/...
{% endhighlight %}
- Note:
-Although it looks as if the savepoints may be moved, it is currently not
possible due to absolute paths in the _metadata file.
-Please follow https://issues.apache.org/jira/browse/FLINK-5778;>FLINK-5778 for
progress on lifting this restriction.
+ 注意:
+虽然看起来好像可以移动 Savepoint ，但由于 _metadata 文件中的绝对路径，目前无法进行保存。
+请按照https://issues.apache.org/jira/browse/FLINK-5778;> FLINK-5778
了解取消此限制的进度。
-
-Note that if you use the `MemoryStateBackend`, metadata *and* savepoint state
will be stored in the `_metadata` file. Since it is self-contained, you may
move the file and restore from any location.
+请注意，如果使用 `MemoryStateBackend`，则元数据*和* Savepoint 状态将存储在`_metadata`文件中。
由于它是自包含的，你可以移动文件并从任何位置恢复。
- Attention: It is discouraged to move or delete the last
savepoint of a running job, because this might interfere with failure-recovery.
Savepoints have side-effects on exactly-once sinks, therefore
- to ensure exactly-once semantics, if there is no checkpoint after the last
savepoint, the savepoint will be used for recovery.
+ 注意: 不建议移动或删除正在运行作业的最后一个 Savepoint
，因为这可能会干扰故障恢复。因此，Savepoint 对完全一次的接收器有副作用，为了确保精确的一次语义，如果在最后一个 Savepoint 之后没有
Checkpoint ，那么将使用 Savepoint 进行恢复。
- Trigger a Savepoint
+
+ 触发 Savepoint
{% highlight shell %}
$ bin/flink savepoint :jobId [:targetDirectory]
{% endhighlight %}
-This will trigger a savepoint for the job with ID `:jobId`, and returns the
path of the created savepoint. You need this path to restore and dispose
savepoints.
+这将触发ID为`：jobId`的作业的Savepoint，并返回创建的 Savepoint 的路径。 你需要此路径来还原和部署 Savepoint 。
- Trigger a Savepoint with YARN
+ 使用 YARN 触发 Savepoint
{% highlight shell %}
$ bin/flink savepoint :jobId [:targetDirectory] -yid :yarnAppId
{% endhighlight %}
-This will trigger a savepoint for the job with ID `:jobId` and YARN
application ID `:yarnAppId`, and returns the path of the created savepoint.
+这将触发 ID 为`：jobId` 和 YARN 应用程序 ID `：yarnAppId`的作业的 Savepoint，并返回创建的 Savepoint
的路径。
- Cancel Job with Savepoint
+ 使用 Savepoint 取消作业
{% highlight shell %}
$ bin/flink cancel -s [:targetDirectory] :jobId
{% endhighlight %}
-This will atomically trigger a savepoint for the job with ID `:jobid` and
cancel the job. Furthermore, you can specify a target file system directory to
store the savepoint in. The directory
[GitHub] [flink] klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh] Translate Savepoints page into Chinese
klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh]
Translate Savepoints page into Chinese
URL: https://github.com/apache/flink/pull/8300#discussion_r281074496
##
File path: docs/ops/state/savepoints.zh.md
##
@@ -78,160 +68,158 @@ source-id | State of StatefulSource
mapper-id | State of StatefulMapper
{% endhighlight %}
-In the above example, the print sink is stateless and hence not part of the
savepoint state. By default, we try to map each entry of the savepoint back to
the new program.
+在上面的示例中，print sink 是无状态的，因此不是 Savepoint 状态的一部分。默认情况下，我们尝试将 Savepoint
的每个条目映射回新程序。
-## Operations
+## 算子
-You can use the [command line client]({{ site.baseurl
}}/ops/cli.html#savepoints) to *trigger savepoints*, *cancel a job with a
savepoint*, *resume from savepoints*, and *dispose savepoints*.
+你可以使用[命令行客户端]({{site.baseurl}}/zh/ops/cli.html#Savepoint)来*触发 Savepoint
*，*取消具有 Savepoint *的作业，*从 Savepoint *恢复，以及*部署 Savepoint *。
-With Flink >= 1.2.0 it is also possible to *resume from savepoints* using the
webui.
+使用 Flink >= 1.2.0，还可以使用 webui *从 Savepoint 恢复*。
-### Triggering Savepoints
+### 触发 Savepoint
-When triggering a savepoint, a new savepoint directory is created where the
data as well as the meta data will be stored. The location of this directory
can be controlled by [configuring a default target directory](#configuration)
or by specifying a custom target directory with the trigger commands (see the
[`:targetDirectory` argument](#trigger-a-savepoint)).
+当触发 Savepoint 时，将创建一个新的 Savepoint
目录，其中存储数据和元数据。可以通过[配置默认目标目录](#configuration)或使用触发器命令指定自定义目标目录(参见[`:targetDirectory
`参数](#trigger-a-savepoint)来控制该目录的位置。
-Attention: The target directory has to be a location
accessible by both the JobManager(s) and TaskManager(s) e.g. a location on a
distributed file-system.
+注意:目标目录必须是 JobManager(s) 和 TaskManager(s)
都可以访问的位置，例如分布式文件系统上的位置。
-For example with a `FsStateBackend` or `RocksDBStateBackend`:
+例如，使用 `FsStateBackend` 或 `RocksDBStateBackend` ：
{% highlight shell %}
-# Savepoint target directory
-/savepoints/
+# Savepoint 目标目录
+/Savepoint/
-# Savepoint directory
-/savepoints/savepoint-:shortjobid-:savepointid/
+# Savepoint 目录
+/Savepoint/savepoint-:shortjobid-:savepointid/
-# Savepoint file contains the checkpoint meta data
-/savepoints/savepoint-:shortjobid-:savepointid/_metadata
+# Savepoint 文件包含 Checkpoint元数据
+/Savepoint/savepoint-:shortjobid-:savepointid/_metadata
-# Savepoint state
-/savepoints/savepoint-:shortjobid-:savepointid/...
+# Savepoint 状态
+/Savepoint/savepoint-:shortjobid-:savepointid/...
{% endhighlight %}
- Note:
-Although it looks as if the savepoints may be moved, it is currently not
possible due to absolute paths in the _metadata file.
-Please follow https://issues.apache.org/jira/browse/FLINK-5778;>FLINK-5778 for
progress on lifting this restriction.
+ 注意:
+虽然看起来好像可以移动 Savepoint ，但由于 _metadata 文件中的绝对路径，目前无法进行保存。
+请按照https://issues.apache.org/jira/browse/FLINK-5778;> FLINK-5778
了解取消此限制的进度。
-
-Note that if you use the `MemoryStateBackend`, metadata *and* savepoint state
will be stored in the `_metadata` file. Since it is self-contained, you may
move the file and restore from any location.
+请注意，如果使用 `MemoryStateBackend`，则元数据*和* Savepoint 状态将存储在`_metadata`文件中。
由于它是自包含的，你可以移动文件并从任何位置恢复。
- Attention: It is discouraged to move or delete the last
savepoint of a running job, because this might interfere with failure-recovery.
Savepoints have side-effects on exactly-once sinks, therefore
- to ensure exactly-once semantics, if there is no checkpoint after the last
savepoint, the savepoint will be used for recovery.
+ 注意: 不建议移动或删除正在运行作业的最后一个 Savepoint
，因为这可能会干扰故障恢复。因此，Savepoint 对完全一次的接收器有副作用，为了确保精确的一次语义，如果在最后一个 Savepoint 之后没有
Checkpoint ，那么将使用 Savepoint 进行恢复。
- Trigger a Savepoint
+
+ 触发 Savepoint
{% highlight shell %}
$ bin/flink savepoint :jobId [:targetDirectory]
{% endhighlight %}
-This will trigger a savepoint for the job with ID `:jobId`, and returns the
path of the created savepoint. You need this path to restore and dispose
savepoints.
+这将触发ID为`：jobId`的作业的Savepoint，并返回创建的 Savepoint 的路径。 你需要此路径来还原和部署 Savepoint 。
- Trigger a Savepoint with YARN
+ 使用 YARN 触发 Savepoint
{% highlight shell %}
$ bin/flink savepoint :jobId [:targetDirectory] -yid :yarnAppId
{% endhighlight %}
-This will trigger a savepoint for the job with ID `:jobId` and YARN
application ID `:yarnAppId`, and returns the path of the created savepoint.
+这将触发 ID 为`：jobId` 和 YARN 应用程序 ID `：yarnAppId`的作业的 Savepoint，并返回创建的 Savepoint
的路径。
- Cancel Job with Savepoint
+ 使用 Savepoint 取消作业
{% highlight shell %}
$ bin/flink cancel -s [:targetDirectory] :jobId
{% endhighlight %}
-This will atomically trigger a savepoint for the job with ID `:jobid` and
cancel the job. Furthermore, you can specify a target file system directory to
store the savepoint in. The directory
[GitHub] [flink] klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh] Translate Savepoints page into Chinese
klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh]
Translate Savepoints page into Chinese
URL: https://github.com/apache/flink/pull/8300#discussion_r281072568
##
File path: docs/ops/state/savepoints.zh.md
##
@@ -78,160 +68,158 @@ source-id | State of StatefulSource
mapper-id | State of StatefulMapper
{% endhighlight %}
-In the above example, the print sink is stateless and hence not part of the
savepoint state. By default, we try to map each entry of the savepoint back to
the new program.
+在上面的示例中，print sink 是无状态的，因此不是 Savepoint 状态的一部分。默认情况下，我们尝试将 Savepoint
的每个条目映射回新程序。
-## Operations
+## 算子
-You can use the [command line client]({{ site.baseurl
}}/ops/cli.html#savepoints) to *trigger savepoints*, *cancel a job with a
savepoint*, *resume from savepoints*, and *dispose savepoints*.
+你可以使用[命令行客户端]({{site.baseurl}}/zh/ops/cli.html#Savepoint)来*触发 Savepoint
*，*取消具有 Savepoint *的作业，*从 Savepoint *恢复，以及*部署 Savepoint *。
-With Flink >= 1.2.0 it is also possible to *resume from savepoints* using the
webui.
+使用 Flink >= 1.2.0，还可以使用 webui *从 Savepoint 恢复*。
-### Triggering Savepoints
+### 触发 Savepoint
-When triggering a savepoint, a new savepoint directory is created where the
data as well as the meta data will be stored. The location of this directory
can be controlled by [configuring a default target directory](#configuration)
or by specifying a custom target directory with the trigger commands (see the
[`:targetDirectory` argument](#trigger-a-savepoint)).
+当触发 Savepoint 时，将创建一个新的 Savepoint
目录，其中存储数据和元数据。可以通过[配置默认目标目录](#configuration)或使用触发器命令指定自定义目标目录(参见[`:targetDirectory
`参数](#trigger-a-savepoint)来控制该目录的位置。
-Attention: The target directory has to be a location
accessible by both the JobManager(s) and TaskManager(s) e.g. a location on a
distributed file-system.
+注意:目标目录必须是 JobManager(s) 和 TaskManager(s)
都可以访问的位置，例如分布式文件系统上的位置。
-For example with a `FsStateBackend` or `RocksDBStateBackend`:
+例如，使用 `FsStateBackend` 或 `RocksDBStateBackend` ：
{% highlight shell %}
-# Savepoint target directory
-/savepoints/
+# Savepoint 目标目录
+/Savepoint/
-# Savepoint directory
-/savepoints/savepoint-:shortjobid-:savepointid/
+# Savepoint 目录
+/Savepoint/savepoint-:shortjobid-:savepointid/
-# Savepoint file contains the checkpoint meta data
-/savepoints/savepoint-:shortjobid-:savepointid/_metadata
+# Savepoint 文件包含 Checkpoint元数据
+/Savepoint/savepoint-:shortjobid-:savepointid/_metadata
-# Savepoint state
-/savepoints/savepoint-:shortjobid-:savepointid/...
+# Savepoint 状态
+/Savepoint/savepoint-:shortjobid-:savepointid/...
{% endhighlight %}
- Note:
-Although it looks as if the savepoints may be moved, it is currently not
possible due to absolute paths in the _metadata file.
-Please follow https://issues.apache.org/jira/browse/FLINK-5778;>FLINK-5778 for
progress on lifting this restriction.
+ 注意:
+虽然看起来好像可以移动 Savepoint ，但由于 _metadata 文件中的绝对路径，目前无法进行保存。
+请按照https://issues.apache.org/jira/browse/FLINK-5778;> FLINK-5778
了解取消此限制的进度。
-
-Note that if you use the `MemoryStateBackend`, metadata *and* savepoint state
will be stored in the `_metadata` file. Since it is self-contained, you may
move the file and restore from any location.
+请注意，如果使用 `MemoryStateBackend`，则元数据*和* Savepoint 状态将存储在`_metadata`文件中。
由于它是自包含的，你可以移动文件并从任何位置恢复。
- Attention: It is discouraged to move or delete the last
savepoint of a running job, because this might interfere with failure-recovery.
Savepoints have side-effects on exactly-once sinks, therefore
- to ensure exactly-once semantics, if there is no checkpoint after the last
savepoint, the savepoint will be used for recovery.
+ 注意: 不建议移动或删除正在运行作业的最后一个 Savepoint
，因为这可能会干扰故障恢复。因此，Savepoint 对完全一次的接收器有副作用，为了确保精确的一次语义，如果在最后一个 Savepoint 之后没有
Checkpoint ，那么将使用 Savepoint 进行恢复。
- Trigger a Savepoint
+
+ 触发 Savepoint
{% highlight shell %}
$ bin/flink savepoint :jobId [:targetDirectory]
{% endhighlight %}
-This will trigger a savepoint for the job with ID `:jobId`, and returns the
path of the created savepoint. You need this path to restore and dispose
savepoints.
+这将触发ID为`：jobId`的作业的Savepoint，并返回创建的 Savepoint 的路径。 你需要此路径来还原和部署 Savepoint 。
- Trigger a Savepoint with YARN
+ 使用 YARN 触发 Savepoint
{% highlight shell %}
$ bin/flink savepoint :jobId [:targetDirectory] -yid :yarnAppId
{% endhighlight %}
-This will trigger a savepoint for the job with ID `:jobId` and YARN
application ID `:yarnAppId`, and returns the path of the created savepoint.
+这将触发 ID 为`：jobId` 和 YARN 应用程序 ID `：yarnAppId`的作业的 Savepoint，并返回创建的 Savepoint
的路径。
- Cancel Job with Savepoint
+ 使用 Savepoint 取消作业
{% highlight shell %}
$ bin/flink cancel -s [:targetDirectory] :jobId
{% endhighlight %}
-This will atomically trigger a savepoint for the job with ID `:jobid` and
cancel the job. Furthermore, you can specify a target file system directory to
store the savepoint in. The directory
[GitHub] [flink] klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh] Translate Savepoints page into Chinese
klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh]
Translate Savepoints page into Chinese
URL: https://github.com/apache/flink/pull/8300#discussion_r281071685
##
File path: docs/ops/state/savepoints.zh.md
##
@@ -78,160 +68,158 @@ source-id | State of StatefulSource
mapper-id | State of StatefulMapper
{% endhighlight %}
-In the above example, the print sink is stateless and hence not part of the
savepoint state. By default, we try to map each entry of the savepoint back to
the new program.
+在上面的示例中，print sink 是无状态的，因此不是 Savepoint 状态的一部分。默认情况下，我们尝试将 Savepoint
的每个条目映射回新程序。
-## Operations
+## 算子
-You can use the [command line client]({{ site.baseurl
}}/ops/cli.html#savepoints) to *trigger savepoints*, *cancel a job with a
savepoint*, *resume from savepoints*, and *dispose savepoints*.
+你可以使用[命令行客户端]({{site.baseurl}}/zh/ops/cli.html#Savepoint)来*触发 Savepoint
*，*取消具有 Savepoint *的作业，*从 Savepoint *恢复，以及*部署 Savepoint *。
-With Flink >= 1.2.0 it is also possible to *resume from savepoints* using the
webui.
+使用 Flink >= 1.2.0，还可以使用 webui *从 Savepoint 恢复*。
-### Triggering Savepoints
+### 触发 Savepoint
-When triggering a savepoint, a new savepoint directory is created where the
data as well as the meta data will be stored. The location of this directory
can be controlled by [configuring a default target directory](#configuration)
or by specifying a custom target directory with the trigger commands (see the
[`:targetDirectory` argument](#trigger-a-savepoint)).
+当触发 Savepoint 时，将创建一个新的 Savepoint
目录，其中存储数据和元数据。可以通过[配置默认目标目录](#configuration)或使用触发器命令指定自定义目标目录(参见[`:targetDirectory
`参数](#trigger-a-savepoint)来控制该目录的位置。
-Attention: The target directory has to be a location
accessible by both the JobManager(s) and TaskManager(s) e.g. a location on a
distributed file-system.
+注意:目标目录必须是 JobManager(s) 和 TaskManager(s)
都可以访问的位置，例如分布式文件系统上的位置。
-For example with a `FsStateBackend` or `RocksDBStateBackend`:
+例如，使用 `FsStateBackend` 或 `RocksDBStateBackend` ：
{% highlight shell %}
-# Savepoint target directory
-/savepoints/
+# Savepoint 目标目录
+/Savepoint/
-# Savepoint directory
-/savepoints/savepoint-:shortjobid-:savepointid/
+# Savepoint 目录
+/Savepoint/savepoint-:shortjobid-:savepointid/
-# Savepoint file contains the checkpoint meta data
-/savepoints/savepoint-:shortjobid-:savepointid/_metadata
+# Savepoint 文件包含 Checkpoint元数据
+/Savepoint/savepoint-:shortjobid-:savepointid/_metadata
-# Savepoint state
-/savepoints/savepoint-:shortjobid-:savepointid/...
+# Savepoint 状态
+/Savepoint/savepoint-:shortjobid-:savepointid/...
{% endhighlight %}
- Note:
-Although it looks as if the savepoints may be moved, it is currently not
possible due to absolute paths in the _metadata file.
-Please follow https://issues.apache.org/jira/browse/FLINK-5778;>FLINK-5778 for
progress on lifting this restriction.
+ 注意:
+虽然看起来好像可以移动 Savepoint ，但由于 _metadata 文件中的绝对路径，目前无法进行保存。
+请按照https://issues.apache.org/jira/browse/FLINK-5778;> FLINK-5778
了解取消此限制的进度。
-
-Note that if you use the `MemoryStateBackend`, metadata *and* savepoint state
will be stored in the `_metadata` file. Since it is self-contained, you may
move the file and restore from any location.
+请注意，如果使用 `MemoryStateBackend`，则元数据*和* Savepoint 状态将存储在`_metadata`文件中。
由于它是自包含的，你可以移动文件并从任何位置恢复。
- Attention: It is discouraged to move or delete the last
savepoint of a running job, because this might interfere with failure-recovery.
Savepoints have side-effects on exactly-once sinks, therefore
- to ensure exactly-once semantics, if there is no checkpoint after the last
savepoint, the savepoint will be used for recovery.
+ 注意: 不建议移动或删除正在运行作业的最后一个 Savepoint
，因为这可能会干扰故障恢复。因此，Savepoint 对完全一次的接收器有副作用，为了确保精确的一次语义，如果在最后一个 Savepoint 之后没有
Checkpoint ，那么将使用 Savepoint 进行恢复。
- Trigger a Savepoint
+
+ 触发 Savepoint
{% highlight shell %}
$ bin/flink savepoint :jobId [:targetDirectory]
{% endhighlight %}
-This will trigger a savepoint for the job with ID `:jobId`, and returns the
path of the created savepoint. You need this path to restore and dispose
savepoints.
+这将触发ID为`：jobId`的作业的Savepoint，并返回创建的 Savepoint 的路径。 你需要此路径来还原和部署 Savepoint 。
- Trigger a Savepoint with YARN
+ 使用 YARN 触发 Savepoint
{% highlight shell %}
$ bin/flink savepoint :jobId [:targetDirectory] -yid :yarnAppId
{% endhighlight %}
-This will trigger a savepoint for the job with ID `:jobId` and YARN
application ID `:yarnAppId`, and returns the path of the created savepoint.
+这将触发 ID 为`：jobId` 和 YARN 应用程序 ID `：yarnAppId`的作业的 Savepoint，并返回创建的 Savepoint
的路径。
- Cancel Job with Savepoint
+ 使用 Savepoint 取消作业
{% highlight shell %}
$ bin/flink cancel -s [:targetDirectory] :jobId
{% endhighlight %}
-This will atomically trigger a savepoint for the job with ID `:jobid` and
cancel the job. Furthermore, you can specify a target file system directory to
store the savepoint in. The directory
[GitHub] [flink] klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh] Translate Savepoints page into Chinese
klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh]
Translate Savepoints page into Chinese
URL: https://github.com/apache/flink/pull/8300#discussion_r280980371
##
File path: docs/ops/state/savepoints.zh.md
##
@@ -25,32 +25,22 @@ under the License.
* toc
{:toc}
-## What is a Savepoint? How is a Savepoint different from a Checkpoint?
+## 什么是 Savepoint ？ Savepoint 与 Checkpoint 有什么不同？
-A Savepoint is a consistent image of the execution state of a streaming job,
created via Flink's [checkpointing mechanism]({{ site.baseurl
}}/internals/stream_checkpointing.html). You can use Savepoints to
stop-and-resume, fork,
-or update your Flink jobs. Savepoints consist of two parts: a directory with
(typically large) binary files on stable storage (e.g. HDFS, S3, ...) and a
(relatively small) meta data file. The files on stable storage represent the
net data of the job's execution state
-image. The meta data file of a Savepoint contains (primarily) pointers to all
files on stable storage that are part of the Savepoint, in form of absolute
paths.
+Savepoint 是依据 Flink [checkpointing 机制]({{ site.baseurl
}}/internals/stream_checkpointing.html)所创建的流作业执行状态的一致镜像。 你可以使用 Savepoint 进行
Flink 作业的停止与重启、fork或者更新。 Savepoint 由两部分组成：稳定存储（列入 HDFS，S3，...)
上包含二进制文件的目录（通常很大），和元数据文件（相对较小）。 稳定存储上的文件表示作业执行状态的数据镜像。 Savepoint
的元数据文件以（绝对路径）的形式包含（主要）指向作为 Savepoint 一部分的稳定存储上的所有文件的指针。
-Attention: In order to allow upgrades between programs and
Flink versions, it is important to check out the following section about assigning IDs to your operators.
+注意: 为了允许程序和 Flink 版本之间的升级，请务必查看以下有关分配算子 ID 的部分 。
+从概念上讲， Flink 的 Savepoint 与 Checkpoint 的不同之处类似于传统数据库中的备份与恢复日志之间的差异。 Checkpoint
的主要目的是为意外失败的作为提供恢复机制。 Checkpoint 的生命周期由 Flink 管理，即 Flink 创建，管理和删除 Checkpoint -
无需用户交互。 作为一种恢复和定期触发的方法，Checkpoint 实现有两个设计目标：i）轻量级创建和 ii）尽可能快地恢复。
可能会利用某些特定的属性来达到这个，例如， 工作代码在执行尝试之间不会改变。 在用户终止作业后，通常会删除 Checkpoint（除非明确配置为保留的
Checkpoint）。
-Conceptually, Flink's Savepoints are different from Checkpoints in a similar
way that backups are different from recovery logs in traditional database
systems. The primary purpose of Checkpoints is to provide a recovery mechanism
in case of
-unexpected job failures. A Checkpoint's lifecycle is managed by Flink, i.e. a
Checkpoint is created, owned, and released by Flink - without user interaction.
As a method of recovery and being periodically triggered, two main
-design goals for the Checkpoint implementation are i) being as lightweight to
create and ii) being as fast to restore from as possible. Optimizations towards
those goals can exploit certain properties, e.g. that the job code
-doesn't change between the execution attempts. Checkpoints are usually dropped
after the job was terminated by the user (except if explicitly configured as
retained Checkpoints).
+ 与此相反、Savepoint 由用户创建，拥有和删除。 他们的用例是计划的，手动备份和恢复。 例如，升级 Flink
版本，调整用户逻辑，改变并行度，以及进行红蓝部署等。 当然，Savepoint 必须在终止工作后继续存在。 从概念上讲，Savepoint
的生成，恢复成本可能更高一些，Savepoint 更多地关注可移植性和对前面提到的作业更改的支持。
-In contrast to all this, Savepoints are created, owned, and deleted by the
user. Their use-case is for planned, manual backup and resume. For example,
this could be an update of your Flink version, changing your job graph,
-changing parallelism, forking a second job like for a red/blue deployment, and
so on. Of course, Savepoints must survive job termination. Conceptually,
Savepoints can be a bit more expensive to produce and restore and focus
-more on portability and support for the previously mentioned changes to the
job.
+除去这些概念上的差异，Checkpoint 和 Savepoint
的当前实现基本上使用相同的代码并生成相同的格式。然而，目前有一个例外，我们可能会在未来引入更多的差异。例外情况是使用 RocksDB 状态后端的增量
Checkpoint。他们使用了一些 RocksDB 内部格式，而不是 Flink 的本机 Savepoint 格式。这使他们成为了与 Savepoint
相比，更轻量级的 Checkpoint 机制的第一个实例。
-Those conceptual differences aside, the current implementations of Checkpoints
and Savepoints are basically using the same code and produce the same format.
However, there is currently one exception from this, and we might
-introduce more differences in the future. The exception are incremental
checkpoints with the RocksDB state backend. They are using some RocksDB
internal format instead of Flink’s native savepoint format. This makes them the
-first instance of a more lightweight checkpointing mechanism, compared to
Savepoints.
+## 分配算子ID
-## Assigning Operator IDs
-
-It is **highly recommended** that you adjust your programs as described in
this section in order to be able to upgrade your programs in the future. The
main required change is to manually specify operator IDs via the
**`uid(String)`** method. These IDs are used to scope the state of each
operator.
+**强烈建议**你按照本节所述调整你的程序，以便将来能够升级你的程序。主要需要的更改是通过**`uid(String)`**方法手动指定算子 ID 。这些
ID 用于限定每个操作符的状态。
Review comment:
I think this sentence can be improved `主要需要的更改是通过**`uid(String)`**方法手动指定算子
ID`
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[GitHub] [flink] klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh] Translate Savepoints page into Chinese
klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh]
Translate Savepoints page into Chinese
URL: https://github.com/apache/flink/pull/8300#discussion_r280980514
##
File path: docs/ops/state/savepoints.zh.md
##
@@ -78,160 +68,158 @@ source-id | State of StatefulSource
mapper-id | State of StatefulMapper
{% endhighlight %}
-In the above example, the print sink is stateless and hence not part of the
savepoint state. By default, we try to map each entry of the savepoint back to
the new program.
+在上面的示例中，print sink 是无状态的，因此不是 Savepoint 状态的一部分。默认情况下，我们尝试将 Savepoint
的每个条目映射回新程序。
-## Operations
+## 算子
-You can use the [command line client]({{ site.baseurl
}}/ops/cli.html#savepoints) to *trigger savepoints*, *cancel a job with a
savepoint*, *resume from savepoints*, and *dispose savepoints*.
+你可以使用[命令行客户端]({{site.baseurl}}/zh/ops/cli.html#Savepoint)来*触发 Savepoint
*，*取消具有 Savepoint *的作业，*从 Savepoint *恢复，以及*部署 Savepoint *。
-With Flink >= 1.2.0 it is also possible to *resume from savepoints* using the
webui.
+使用 Flink >= 1.2.0，还可以使用 webui *从 Savepoint 恢复*。
-### Triggering Savepoints
+### 触发 Savepoint
-When triggering a savepoint, a new savepoint directory is created where the
data as well as the meta data will be stored. The location of this directory
can be controlled by [configuring a default target directory](#configuration)
or by specifying a custom target directory with the trigger commands (see the
[`:targetDirectory` argument](#trigger-a-savepoint)).
+当触发 Savepoint 时，将创建一个新的 Savepoint
目录，其中存储数据和元数据。可以通过[配置默认目标目录](#configuration)或使用触发器命令指定自定义目标目录(参见[`:targetDirectory
`参数](#trigger-a-savepoint)来控制该目录的位置。
-Attention: The target directory has to be a location
accessible by both the JobManager(s) and TaskManager(s) e.g. a location on a
distributed file-system.
+注意:目标目录必须是 JobManager(s) 和 TaskManager(s)
都可以访问的位置，例如分布式文件系统上的位置。
-For example with a `FsStateBackend` or `RocksDBStateBackend`:
+例如，使用 `FsStateBackend` 或 `RocksDBStateBackend` ：
{% highlight shell %}
-# Savepoint target directory
-/savepoints/
+# Savepoint 目标目录
+/Savepoint/
-# Savepoint directory
-/savepoints/savepoint-:shortjobid-:savepointid/
+# Savepoint 目录
+/Savepoint/savepoint-:shortjobid-:savepointid/
-# Savepoint file contains the checkpoint meta data
-/savepoints/savepoint-:shortjobid-:savepointid/_metadata
+# Savepoint 文件包含 Checkpoint元数据
+/Savepoint/savepoint-:shortjobid-:savepointid/_metadata
-# Savepoint state
-/savepoints/savepoint-:shortjobid-:savepointid/...
+# Savepoint 状态
+/Savepoint/savepoint-:shortjobid-:savepointid/...
{% endhighlight %}
- Note:
-Although it looks as if the savepoints may be moved, it is currently not
possible due to absolute paths in the _metadata file.
-Please follow https://issues.apache.org/jira/browse/FLINK-5778;>FLINK-5778 for
progress on lifting this restriction.
+ 注意:
+虽然看起来好像可以移动 Savepoint ，但由于 _metadata 文件中的绝对路径，目前无法进行保存。
Review comment:
`但由于 _metadata 文件中的绝对路径，目前无法进行保存。` --> `但由于 _metadata
中保存的是绝对路径，因此暂时不支持。
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[GitHub] [flink] klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh] Translate Savepoints page into Chinese
klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh]
Translate Savepoints page into Chinese
URL: https://github.com/apache/flink/pull/8300#discussion_r280980459
##
File path: docs/ops/state/savepoints.zh.md
##
@@ -78,160 +68,158 @@ source-id | State of StatefulSource
mapper-id | State of StatefulMapper
{% endhighlight %}
-In the above example, the print sink is stateless and hence not part of the
savepoint state. By default, we try to map each entry of the savepoint back to
the new program.
+在上面的示例中，print sink 是无状态的，因此不是 Savepoint 状态的一部分。默认情况下，我们尝试将 Savepoint
的每个条目映射回新程序。
-## Operations
+## 算子
-You can use the [command line client]({{ site.baseurl
}}/ops/cli.html#savepoints) to *trigger savepoints*, *cancel a job with a
savepoint*, *resume from savepoints*, and *dispose savepoints*.
+你可以使用[命令行客户端]({{site.baseurl}}/zh/ops/cli.html#Savepoint)来*触发 Savepoint
*，*取消具有 Savepoint *的作业，*从 Savepoint *恢复，以及*部署 Savepoint *。
-With Flink >= 1.2.0 it is also possible to *resume from savepoints* using the
webui.
+使用 Flink >= 1.2.0，还可以使用 webui *从 Savepoint 恢复*。
Review comment:
`使用 Flink >= 1.2.0` --> `从 Flink 1.2.0 开始`
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[GitHub] [flink] klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh] Translate Savepoints page into Chinese
klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh]
Translate Savepoints page into Chinese
URL: https://github.com/apache/flink/pull/8300#discussion_r280980436
##
File path: docs/ops/state/savepoints.zh.md
##
@@ -78,160 +68,158 @@ source-id | State of StatefulSource
mapper-id | State of StatefulMapper
{% endhighlight %}
-In the above example, the print sink is stateless and hence not part of the
savepoint state. By default, we try to map each entry of the savepoint back to
the new program.
+在上面的示例中，print sink 是无状态的，因此不是 Savepoint 状态的一部分。默认情况下，我们尝试将 Savepoint
的每个条目映射回新程序。
-## Operations
+## 算子
-You can use the [command line client]({{ site.baseurl
}}/ops/cli.html#savepoints) to *trigger savepoints*, *cancel a job with a
savepoint*, *resume from savepoints*, and *dispose savepoints*.
+你可以使用[命令行客户端]({{site.baseurl}}/zh/ops/cli.html#Savepoint)来*触发 Savepoint
*，*取消具有 Savepoint *的作业，*从 Savepoint *恢复，以及*部署 Savepoint *。
Review comment:
`*取消具有 Savepoint *的作业` --> `*触发 Savepoint 并取消作业*`
`*部署 Savepoint *` --> `删除 Savepoint`?
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[GitHub] [flink] klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh] Translate Savepoints page into Chinese
klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh]
Translate Savepoints page into Chinese
URL: https://github.com/apache/flink/pull/8300#discussion_r280980604
##
File path: docs/ops/state/savepoints.zh.md
##
@@ -78,160 +68,158 @@ source-id | State of StatefulSource
mapper-id | State of StatefulMapper
{% endhighlight %}
-In the above example, the print sink is stateless and hence not part of the
savepoint state. By default, we try to map each entry of the savepoint back to
the new program.
+在上面的示例中，print sink 是无状态的，因此不是 Savepoint 状态的一部分。默认情况下，我们尝试将 Savepoint
的每个条目映射回新程序。
-## Operations
+## 算子
-You can use the [command line client]({{ site.baseurl
}}/ops/cli.html#savepoints) to *trigger savepoints*, *cancel a job with a
savepoint*, *resume from savepoints*, and *dispose savepoints*.
+你可以使用[命令行客户端]({{site.baseurl}}/zh/ops/cli.html#Savepoint)来*触发 Savepoint
*，*取消具有 Savepoint *的作业，*从 Savepoint *恢复，以及*部署 Savepoint *。
-With Flink >= 1.2.0 it is also possible to *resume from savepoints* using the
webui.
+使用 Flink >= 1.2.0，还可以使用 webui *从 Savepoint 恢复*。
-### Triggering Savepoints
+### 触发 Savepoint
-When triggering a savepoint, a new savepoint directory is created where the
data as well as the meta data will be stored. The location of this directory
can be controlled by [configuring a default target directory](#configuration)
or by specifying a custom target directory with the trigger commands (see the
[`:targetDirectory` argument](#trigger-a-savepoint)).
+当触发 Savepoint 时，将创建一个新的 Savepoint
目录，其中存储数据和元数据。可以通过[配置默认目标目录](#configuration)或使用触发器命令指定自定义目标目录(参见[`:targetDirectory
`参数](#trigger-a-savepoint)来控制该目录的位置。
-Attention: The target directory has to be a location
accessible by both the JobManager(s) and TaskManager(s) e.g. a location on a
distributed file-system.
+注意:目标目录必须是 JobManager(s) 和 TaskManager(s)
都可以访问的位置，例如分布式文件系统上的位置。
-For example with a `FsStateBackend` or `RocksDBStateBackend`:
+例如，使用 `FsStateBackend` 或 `RocksDBStateBackend` ：
{% highlight shell %}
-# Savepoint target directory
-/savepoints/
+# Savepoint 目标目录
+/Savepoint/
-# Savepoint directory
-/savepoints/savepoint-:shortjobid-:savepointid/
+# Savepoint 目录
+/Savepoint/savepoint-:shortjobid-:savepointid/
-# Savepoint file contains the checkpoint meta data
-/savepoints/savepoint-:shortjobid-:savepointid/_metadata
+# Savepoint 文件包含 Checkpoint元数据
+/Savepoint/savepoint-:shortjobid-:savepointid/_metadata
-# Savepoint state
-/savepoints/savepoint-:shortjobid-:savepointid/...
+# Savepoint 状态
+/Savepoint/savepoint-:shortjobid-:savepointid/...
{% endhighlight %}
- Note:
-Although it looks as if the savepoints may be moved, it is currently not
possible due to absolute paths in the _metadata file.
-Please follow https://issues.apache.org/jira/browse/FLINK-5778;>FLINK-5778 for
progress on lifting this restriction.
+ 注意:
+虽然看起来好像可以移动 Savepoint ，但由于 _metadata 文件中的绝对路径，目前无法进行保存。
+请按照https://issues.apache.org/jira/browse/FLINK-5778;> FLINK-5778
了解取消此限制的进度。
-
-Note that if you use the `MemoryStateBackend`, metadata *and* savepoint state
will be stored in the `_metadata` file. Since it is self-contained, you may
move the file and restore from any location.
+请注意，如果使用 `MemoryStateBackend`，则元数据*和* Savepoint 状态将存储在`_metadata`文件中。
由于它是自包含的，你可以移动文件并从任何位置恢复。
- Attention: It is discouraged to move or delete the last
savepoint of a running job, because this might interfere with failure-recovery.
Savepoints have side-effects on exactly-once sinks, therefore
- to ensure exactly-once semantics, if there is no checkpoint after the last
savepoint, the savepoint will be used for recovery.
+ 注意: 不建议移动或删除正在运行作业的最后一个 Savepoint
，因为这可能会干扰故障恢复。因此，Savepoint 对完全一次的接收器有副作用，为了确保精确的一次语义，如果在最后一个 Savepoint 之后没有
Checkpoint ，那么将使用 Savepoint 进行恢复。
Review comment:
`完全一次` --> `精确一次`
`精确的一次语义` --> `精确一次的语义`
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[GitHub] [flink] klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh] Translate Savepoints page into Chinese
klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh]
Translate Savepoints page into Chinese
URL: https://github.com/apache/flink/pull/8300#discussion_r280980635
##
File path: docs/ops/state/savepoints.zh.md
##
@@ -78,160 +68,158 @@ source-id | State of StatefulSource
mapper-id | State of StatefulMapper
{% endhighlight %}
-In the above example, the print sink is stateless and hence not part of the
savepoint state. By default, we try to map each entry of the savepoint back to
the new program.
+在上面的示例中，print sink 是无状态的，因此不是 Savepoint 状态的一部分。默认情况下，我们尝试将 Savepoint
的每个条目映射回新程序。
-## Operations
+## 算子
-You can use the [command line client]({{ site.baseurl
}}/ops/cli.html#savepoints) to *trigger savepoints*, *cancel a job with a
savepoint*, *resume from savepoints*, and *dispose savepoints*.
+你可以使用[命令行客户端]({{site.baseurl}}/zh/ops/cli.html#Savepoint)来*触发 Savepoint
*，*取消具有 Savepoint *的作业，*从 Savepoint *恢复，以及*部署 Savepoint *。
-With Flink >= 1.2.0 it is also possible to *resume from savepoints* using the
webui.
+使用 Flink >= 1.2.0，还可以使用 webui *从 Savepoint 恢复*。
-### Triggering Savepoints
+### 触发 Savepoint
-When triggering a savepoint, a new savepoint directory is created where the
data as well as the meta data will be stored. The location of this directory
can be controlled by [configuring a default target directory](#configuration)
or by specifying a custom target directory with the trigger commands (see the
[`:targetDirectory` argument](#trigger-a-savepoint)).
+当触发 Savepoint 时，将创建一个新的 Savepoint
目录，其中存储数据和元数据。可以通过[配置默认目标目录](#configuration)或使用触发器命令指定自定义目标目录(参见[`:targetDirectory
`参数](#trigger-a-savepoint)来控制该目录的位置。
-Attention: The target directory has to be a location
accessible by both the JobManager(s) and TaskManager(s) e.g. a location on a
distributed file-system.
+注意:目标目录必须是 JobManager(s) 和 TaskManager(s)
都可以访问的位置，例如分布式文件系统上的位置。
-For example with a `FsStateBackend` or `RocksDBStateBackend`:
+例如，使用 `FsStateBackend` 或 `RocksDBStateBackend` ：
{% highlight shell %}
-# Savepoint target directory
-/savepoints/
+# Savepoint 目标目录
+/Savepoint/
-# Savepoint directory
-/savepoints/savepoint-:shortjobid-:savepointid/
+# Savepoint 目录
+/Savepoint/savepoint-:shortjobid-:savepointid/
-# Savepoint file contains the checkpoint meta data
-/savepoints/savepoint-:shortjobid-:savepointid/_metadata
+# Savepoint 文件包含 Checkpoint元数据
+/Savepoint/savepoint-:shortjobid-:savepointid/_metadata
-# Savepoint state
-/savepoints/savepoint-:shortjobid-:savepointid/...
+# Savepoint 状态
+/Savepoint/savepoint-:shortjobid-:savepointid/...
{% endhighlight %}
- Note:
-Although it looks as if the savepoints may be moved, it is currently not
possible due to absolute paths in the _metadata file.
-Please follow https://issues.apache.org/jira/browse/FLINK-5778;>FLINK-5778 for
progress on lifting this restriction.
+ 注意:
+虽然看起来好像可以移动 Savepoint ，但由于 _metadata 文件中的绝对路径，目前无法进行保存。
+请按照https://issues.apache.org/jira/browse/FLINK-5778;> FLINK-5778
了解取消此限制的进度。
-
-Note that if you use the `MemoryStateBackend`, metadata *and* savepoint state
will be stored in the `_metadata` file. Since it is self-contained, you may
move the file and restore from any location.
+请注意，如果使用 `MemoryStateBackend`，则元数据*和* Savepoint 状态将存储在`_metadata`文件中。
由于它是自包含的，你可以移动文件并从任何位置恢复。
- Attention: It is discouraged to move or delete the last
savepoint of a running job, because this might interfere with failure-recovery.
Savepoints have side-effects on exactly-once sinks, therefore
- to ensure exactly-once semantics, if there is no checkpoint after the last
savepoint, the savepoint will be used for recovery.
+ 注意: 不建议移动或删除正在运行作业的最后一个 Savepoint
，因为这可能会干扰故障恢复。因此，Savepoint 对完全一次的接收器有副作用，为了确保精确的一次语义，如果在最后一个 Savepoint 之后没有
Checkpoint ，那么将使用 Savepoint 进行恢复。
- Trigger a Savepoint
+
+ 触发 Savepoint
{% highlight shell %}
$ bin/flink savepoint :jobId [:targetDirectory]
{% endhighlight %}
-This will trigger a savepoint for the job with ID `:jobId`, and returns the
path of the created savepoint. You need this path to restore and dispose
savepoints.
+这将触发ID为`：jobId`的作业的Savepoint，并返回创建的 Savepoint 的路径。 你需要此路径来还原和部署 Savepoint 。
- Trigger a Savepoint with YARN
+ 使用 YARN 触发 Savepoint
{% highlight shell %}
$ bin/flink savepoint :jobId [:targetDirectory] -yid :yarnAppId
{% endhighlight %}
-This will trigger a savepoint for the job with ID `:jobId` and YARN
application ID `:yarnAppId`, and returns the path of the created savepoint.
+这将触发 ID 为`：jobId` 和 YARN 应用程序 ID `：yarnAppId`的作业的 Savepoint，并返回创建的 Savepoint
的路径。
- Cancel Job with Savepoint
+ 使用 Savepoint 取消作业
{% highlight shell %}
$ bin/flink cancel -s [:targetDirectory] :jobId
{% endhighlight %}
-This will atomically trigger a savepoint for the job with ID `:jobid` and
cancel the job. Furthermore, you can specify a target file system directory to
store the savepoint in. The directory
[GitHub] [flink] klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh] Translate Savepoints page into Chinese
klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh]
Translate Savepoints page into Chinese
URL: https://github.com/apache/flink/pull/8300#discussion_r279629649
##
File path: docs/ops/state/savepoints.zh.md
##
@@ -25,32 +25,23 @@ under the License.
* toc
{:toc}
-## What is a Savepoint? How is a Savepoint different from a Checkpoint?
+## 什么是 Savepoint ？ Savepoint 与 Checkpoint 有什么不同？
-A Savepoint is a consistent image of the execution state of a streaming job,
created via Flink's [checkpointing mechanism]({{ site.baseurl
}}/internals/stream_checkpointing.html). You can use Savepoints to
stop-and-resume, fork,
-or update your Flink jobs. Savepoints consist of two parts: a directory with
(typically large) binary files on stable storage (e.g. HDFS, S3, ...) and a
(relatively small) meta data file. The files on stable storage represent the
net data of the job's execution state
-image. The meta data file of a Savepoint contains (primarily) pointers to all
files on stable storage that are part of the Savepoint, in form of absolute
paths.
+Savepoint 是依据 Flink [checkpointing 机制]({{ site.baseurl
}}/internals/stream_checkpointing.html)所创建的流作业执行状态的一致镜像。 你可以使用 Savepoint 进行
Flink 作业的停止与重启、fork或者更新。 Savepoint 由两部分组成：具有稳定存储（例如 HDFS，S3，...）上的（通常是大的）二进制文件
--> 稳定存储（例如 HDFS、S3等）上包含二进制文件的目录（通常很大）和（相对较小的）元数据文件。 稳定存储上的文件表示作业执行状态的数据镜像。
Savepoint 的元数据文件以（绝对路径）的形式包含（主要）指向作为 Savepoint 一部分的稳定存储上的所有文件的指针。
Review comment:
may be "具有稳定存储（例如 HDFS，S3，...）上的（通常是大的）二进制文件 --> 稳定存储（例如
HDFS、S3等）上包含二进制文件的目录（通常很大）和（相对较小的）元数据文件。"
can change to "稳定存储（列入 HDFS，S3，...) 上包含二进制文件的目录（通常很大），和元数据文件（相对较小）"
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[GitHub] [flink] klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh] Translate Savepoints page into Chinese
klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh]
Translate Savepoints page into Chinese
URL: https://github.com/apache/flink/pull/8300#discussion_r279630256
##
File path: docs/ops/state/savepoints.zh.md
##
@@ -25,32 +25,23 @@ under the License.
* toc
{:toc}
-## What is a Savepoint? How is a Savepoint different from a Checkpoint?
+## 什么是 Savepoint ？ Savepoint 与 Checkpoint 有什么不同？
-A Savepoint is a consistent image of the execution state of a streaming job,
created via Flink's [checkpointing mechanism]({{ site.baseurl
}}/internals/stream_checkpointing.html). You can use Savepoints to
stop-and-resume, fork,
-or update your Flink jobs. Savepoints consist of two parts: a directory with
(typically large) binary files on stable storage (e.g. HDFS, S3, ...) and a
(relatively small) meta data file. The files on stable storage represent the
net data of the job's execution state
-image. The meta data file of a Savepoint contains (primarily) pointers to all
files on stable storage that are part of the Savepoint, in form of absolute
paths.
+Savepoint 是依据 Flink [checkpointing 机制]({{ site.baseurl
}}/internals/stream_checkpointing.html)所创建的流作业执行状态的一致镜像。 你可以使用 Savepoint 进行
Flink 作业的停止与重启、fork或者更新。 Savepoint 由两部分组成：具有稳定存储（例如 HDFS，S3，...）上的（通常是大的）二进制文件
--> 稳定存储（例如 HDFS、S3等）上包含二进制文件的目录（通常很大）和（相对较小的）元数据文件。 稳定存储上的文件表示作业执行状态的数据镜像。
Savepoint 的元数据文件以（绝对路径）的形式包含（主要）指向作为 Savepoint 一部分的稳定存储上的所有文件的指针。
-Attention: In order to allow upgrades between programs and
Flink versions, it is important to check out the following section about assigning IDs to your operators.
+注意: 为了允许程序和 Flink 版本之间的升级，请务必查看以下有关分配算子 ID 的部分 。
+从概念上讲， Flink 的 Savepoint 与 Checkpoint 的不同之处类似于传统数据库中的备份与恢复日志之间的差异。
Checkpoint的主要目的是为意外失败的作为提供恢复机制。 Checkpoint 的生命周期由Flink管理，即 Flink 创建，拥有和发布
Checkpoint - 无需用户交互。 作为一种恢复和定期触发的方法，Checkpoint 实现有两个设计目标：i）轻量级创建和 ii）尽可能快地恢复。
针对这些目标的优化可以利用某些属性，例如， 工作代码在执行尝试之间不会改变。 在用户终止作业后，通常会删除 Checkpoint（除非明确配置为保留的
Checkpoint）。
Review comment:
`即 Flink 创建，拥有和发布 Checkpoint` --> `Flink 创建，管理和删除 Checkpoint`
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[GitHub] [flink] klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh] Translate Savepoints page into Chinese
klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh]
Translate Savepoints page into Chinese
URL: https://github.com/apache/flink/pull/8300#discussion_r279630607
##
File path: docs/ops/state/savepoints.zh.md
##
@@ -25,32 +25,23 @@ under the License.
* toc
{:toc}
-## What is a Savepoint? How is a Savepoint different from a Checkpoint?
+## 什么是 Savepoint ？ Savepoint 与 Checkpoint 有什么不同？
-A Savepoint is a consistent image of the execution state of a streaming job,
created via Flink's [checkpointing mechanism]({{ site.baseurl
}}/internals/stream_checkpointing.html). You can use Savepoints to
stop-and-resume, fork,
-or update your Flink jobs. Savepoints consist of two parts: a directory with
(typically large) binary files on stable storage (e.g. HDFS, S3, ...) and a
(relatively small) meta data file. The files on stable storage represent the
net data of the job's execution state
-image. The meta data file of a Savepoint contains (primarily) pointers to all
files on stable storage that are part of the Savepoint, in form of absolute
paths.
+Savepoint 是依据 Flink [checkpointing 机制]({{ site.baseurl
}}/internals/stream_checkpointing.html)所创建的流作业执行状态的一致镜像。 你可以使用 Savepoint 进行
Flink 作业的停止与重启、fork或者更新。 Savepoint 由两部分组成：具有稳定存储（例如 HDFS，S3，...）上的（通常是大的）二进制文件
--> 稳定存储（例如 HDFS、S3等）上包含二进制文件的目录（通常很大）和（相对较小的）元数据文件。 稳定存储上的文件表示作业执行状态的数据镜像。
Savepoint 的元数据文件以（绝对路径）的形式包含（主要）指向作为 Savepoint 一部分的稳定存储上的所有文件的指针。
-Attention: In order to allow upgrades between programs and
Flink versions, it is important to check out the following section about assigning IDs to your operators.
+注意: 为了允许程序和 Flink 版本之间的升级，请务必查看以下有关分配算子 ID 的部分 。
+从概念上讲， Flink 的 Savepoint 与 Checkpoint 的不同之处类似于传统数据库中的备份与恢复日志之间的差异。
Checkpoint的主要目的是为意外失败的作为提供恢复机制。 Checkpoint 的生命周期由Flink管理，即 Flink 创建，拥有和发布
Checkpoint - 无需用户交互。 作为一种恢复和定期触发的方法，Checkpoint 实现有两个设计目标：i）轻量级创建和 ii）尽可能快地恢复。
针对这些目标的优化可以利用某些属性，例如， 工作代码在执行尝试之间不会改变。 在用户终止作业后，通常会删除 Checkpoint（除非明确配置为保留的
Checkpoint）。
Review comment:
`针对这些目标的优化可以利用某些属性` --> `可能会利用某些特定的属性来达到这个`
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[GitHub] [flink] klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh] Translate Savepoints page into Chinese
klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh]
Translate Savepoints page into Chinese
URL: https://github.com/apache/flink/pull/8300#discussion_r279629929
##
File path: docs/ops/state/savepoints.zh.md
##
@@ -25,32 +25,23 @@ under the License.
* toc
{:toc}
-## What is a Savepoint? How is a Savepoint different from a Checkpoint?
+## 什么是 Savepoint ？ Savepoint 与 Checkpoint 有什么不同？
-A Savepoint is a consistent image of the execution state of a streaming job,
created via Flink's [checkpointing mechanism]({{ site.baseurl
}}/internals/stream_checkpointing.html). You can use Savepoints to
stop-and-resume, fork,
-or update your Flink jobs. Savepoints consist of two parts: a directory with
(typically large) binary files on stable storage (e.g. HDFS, S3, ...) and a
(relatively small) meta data file. The files on stable storage represent the
net data of the job's execution state
-image. The meta data file of a Savepoint contains (primarily) pointers to all
files on stable storage that are part of the Savepoint, in form of absolute
paths.
+Savepoint 是依据 Flink [checkpointing 机制]({{ site.baseurl
}}/internals/stream_checkpointing.html)所创建的流作业执行状态的一致镜像。 你可以使用 Savepoint 进行
Flink 作业的停止与重启、fork或者更新。 Savepoint 由两部分组成：具有稳定存储（例如 HDFS，S3，...）上的（通常是大的）二进制文件
--> 稳定存储（例如 HDFS、S3等）上包含二进制文件的目录（通常很大）和（相对较小的）元数据文件。 稳定存储上的文件表示作业执行状态的数据镜像。
Savepoint 的元数据文件以（绝对路径）的形式包含（主要）指向作为 Savepoint 一部分的稳定存储上的所有文件的指针。
-Attention: In order to allow upgrades between programs and
Flink versions, it is important to check out the following section about assigning IDs to your operators.
+注意: 为了允许程序和 Flink 版本之间的升级，请务必查看以下有关分配算子 ID 的部分 。
+从概念上讲， Flink 的 Savepoint 与 Checkpoint 的不同之处类似于传统数据库中的备份与恢复日志之间的差异。
Checkpoint的主要目的是为意外失败的作为提供恢复机制。 Checkpoint 的生命周期由Flink管理，即 Flink 创建，拥有和发布
Checkpoint - 无需用户交互。 作为一种恢复和定期触发的方法，Checkpoint 实现有两个设计目标：i）轻量级创建和 ii）尽可能快地恢复。
针对这些目标的优化可以利用某些属性，例如， 工作代码在执行尝试之间不会改变。 在用户终止作业后，通常会删除 Checkpoint（除非明确配置为保留的
Checkpoint）。
Review comment:
`Checkpoint的主要目的是为意外` --> `Checkpoint 的主要目的是为意外`
`生命周期由Flink管理` --> `生命周期由 Flink 管理`
and all the other places.
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[GitHub] [flink] klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh] Translate Savepoints page into Chinese
klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh]
Translate Savepoints page into Chinese
URL: https://github.com/apache/flink/pull/8300#discussion_r279632468
##
File path: docs/ops/state/savepoints.zh.md
##
@@ -25,32 +25,23 @@ under the License.
* toc
{:toc}
-## What is a Savepoint? How is a Savepoint different from a Checkpoint?
+## 什么是 Savepoint ？ Savepoint 与 Checkpoint 有什么不同？
-A Savepoint is a consistent image of the execution state of a streaming job,
created via Flink's [checkpointing mechanism]({{ site.baseurl
}}/internals/stream_checkpointing.html). You can use Savepoints to
stop-and-resume, fork,
-or update your Flink jobs. Savepoints consist of two parts: a directory with
(typically large) binary files on stable storage (e.g. HDFS, S3, ...) and a
(relatively small) meta data file. The files on stable storage represent the
net data of the job's execution state
-image. The meta data file of a Savepoint contains (primarily) pointers to all
files on stable storage that are part of the Savepoint, in form of absolute
paths.
+Savepoint 是依据 Flink [checkpointing 机制]({{ site.baseurl
}}/internals/stream_checkpointing.html)所创建的流作业执行状态的一致镜像。 你可以使用 Savepoint 进行
Flink 作业的停止与重启、fork或者更新。 Savepoint 由两部分组成：具有稳定存储（例如 HDFS，S3，...）上的（通常是大的）二进制文件
--> 稳定存储（例如 HDFS、S3等）上包含二进制文件的目录（通常很大）和（相对较小的）元数据文件。 稳定存储上的文件表示作业执行状态的数据镜像。
Savepoint 的元数据文件以（绝对路径）的形式包含（主要）指向作为 Savepoint 一部分的稳定存储上的所有文件的指针。
-Attention: In order to allow upgrades between programs and
Flink versions, it is important to check out the following section about assigning IDs to your operators.
+注意: 为了允许程序和 Flink 版本之间的升级，请务必查看以下有关分配算子 ID 的部分 。
+从概念上讲， Flink 的 Savepoint 与 Checkpoint 的不同之处类似于传统数据库中的备份与恢复日志之间的差异。
Checkpoint的主要目的是为意外失败的作为提供恢复机制。 Checkpoint 的生命周期由Flink管理，即 Flink 创建，拥有和发布
Checkpoint - 无需用户交互。 作为一种恢复和定期触发的方法，Checkpoint 实现有两个设计目标：i）轻量级创建和 ii）尽可能快地恢复。
针对这些目标的优化可以利用某些属性，例如， 工作代码在执行尝试之间不会改变。 在用户终止作业后，通常会删除 Checkpoint（除非明确配置为保留的
Checkpoint）。
-Conceptually, Flink's Savepoints are different from Checkpoints in a similar
way that backups are different from recovery logs in traditional database
systems. The primary purpose of Checkpoints is to provide a recovery mechanism
in case of
-unexpected job failures. A Checkpoint's lifecycle is managed by Flink, i.e. a
Checkpoint is created, owned, and released by Flink - without user interaction.
As a method of recovery and being periodically triggered, two main
-design goals for the Checkpoint implementation are i) being as lightweight to
create and ii) being as fast to restore from as possible. Optimizations towards
those goals can exploit certain properties, e.g. that the job code
-doesn't change between the execution attempts. Checkpoints are usually dropped
after the job was terminated by the user (except if explicitly configured as
retained Checkpoints).
+ 与此相反、Savepoint 由用户创建，拥有和删除。 他们的用例是计划的，手动备份和恢复。 例如，这可能是你的Flink
版本的更新，更改你的工作图，改变并行性，分配第二个工作，如红色/蓝色部署，等等。 当然，Savepoint 必须在终止工作后继续存在。
从概念上讲，Savepoint 的生成，恢复和关注成本可能更高一些
+更多关于可移植性和对前面提到的工作变化的支持。
Review comment:
I think this line should append after the previous line.
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[GitHub] [flink] klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh] Translate Savepoints page into Chinese
klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh]
Translate Savepoints page into Chinese
URL: https://github.com/apache/flink/pull/8300#discussion_r279632593
##
File path: docs/ops/state/savepoints.zh.md
##
@@ -25,32 +25,23 @@ under the License.
* toc
{:toc}
-## What is a Savepoint? How is a Savepoint different from a Checkpoint?
+## 什么是 Savepoint ？ Savepoint 与 Checkpoint 有什么不同？
-A Savepoint is a consistent image of the execution state of a streaming job,
created via Flink's [checkpointing mechanism]({{ site.baseurl
}}/internals/stream_checkpointing.html). You can use Savepoints to
stop-and-resume, fork,
-or update your Flink jobs. Savepoints consist of two parts: a directory with
(typically large) binary files on stable storage (e.g. HDFS, S3, ...) and a
(relatively small) meta data file. The files on stable storage represent the
net data of the job's execution state
-image. The meta data file of a Savepoint contains (primarily) pointers to all
files on stable storage that are part of the Savepoint, in form of absolute
paths.
+Savepoint 是依据 Flink [checkpointing 机制]({{ site.baseurl
}}/internals/stream_checkpointing.html)所创建的流作业执行状态的一致镜像。 你可以使用 Savepoint 进行
Flink 作业的停止与重启、fork或者更新。 Savepoint 由两部分组成：具有稳定存储（例如 HDFS，S3，...）上的（通常是大的）二进制文件
--> 稳定存储（例如 HDFS、S3等）上包含二进制文件的目录（通常很大）和（相对较小的）元数据文件。 稳定存储上的文件表示作业执行状态的数据镜像。
Savepoint 的元数据文件以（绝对路径）的形式包含（主要）指向作为 Savepoint 一部分的稳定存储上的所有文件的指针。
-Attention: In order to allow upgrades between programs and
Flink versions, it is important to check out the following section about assigning IDs to your operators.
+注意: 为了允许程序和 Flink 版本之间的升级，请务必查看以下有关分配算子 ID 的部分 。
+从概念上讲， Flink 的 Savepoint 与 Checkpoint 的不同之处类似于传统数据库中的备份与恢复日志之间的差异。
Checkpoint的主要目的是为意外失败的作为提供恢复机制。 Checkpoint 的生命周期由Flink管理，即 Flink 创建，拥有和发布
Checkpoint - 无需用户交互。 作为一种恢复和定期触发的方法，Checkpoint 实现有两个设计目标：i）轻量级创建和 ii）尽可能快地恢复。
针对这些目标的优化可以利用某些属性，例如， 工作代码在执行尝试之间不会改变。 在用户终止作业后，通常会删除 Checkpoint（除非明确配置为保留的
Checkpoint）。
-Conceptually, Flink's Savepoints are different from Checkpoints in a similar
way that backups are different from recovery logs in traditional database
systems. The primary purpose of Checkpoints is to provide a recovery mechanism
in case of
-unexpected job failures. A Checkpoint's lifecycle is managed by Flink, i.e. a
Checkpoint is created, owned, and released by Flink - without user interaction.
As a method of recovery and being periodically triggered, two main
-design goals for the Checkpoint implementation are i) being as lightweight to
create and ii) being as fast to restore from as possible. Optimizations towards
those goals can exploit certain properties, e.g. that the job code
-doesn't change between the execution attempts. Checkpoints are usually dropped
after the job was terminated by the user (except if explicitly configured as
retained Checkpoints).
+ 与此相反、Savepoint 由用户创建，拥有和删除。 他们的用例是计划的，手动备份和恢复。 例如，这可能是你的Flink
版本的更新，更改你的工作图，改变并行性，分配第二个工作，如红色/蓝色部署，等等。 当然，Savepoint 必须在终止工作后继续存在。
从概念上讲，Savepoint 的生成，恢复和关注成本可能更高一些
+更多关于可移植性和对前面提到的工作变化的支持。
-In contrast to all this, Savepoints are created, owned, and deleted by the
user. Their use-case is for planned, manual backup and resume. For example,
this could be an update of your Flink version, changing your job graph,
-changing parallelism, forking a second job like for a red/blue deployment, and
so on. Of course, Savepoints must survive job termination. Conceptually,
Savepoints can be a bit more expensive to produce and restore and focus
-more on portability and support for the previously mentioned changes to the
job.
+除去这些概念上的差异，Checkpoint 和 Savepoint
的当前实现基本上使用相同的代码并生成相同的格式。然而，目前有一个例外，我们可能会在未来引入更多的差异。例外情况是使用 RocksDB 状态后端的增量
Checkpoint。他们使用了一些 RocksDB 内部格式，而不是 Flink 的本机 Savepoint 格式。这使他们成为了与 Savepoint
相比，更轻量级的 Checkpoint机制的第一个实例。
Review comment:
`Checkpoint机制的第一个实例` -> `Checkpoint 机制的第一个实例`
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[GitHub] [flink] klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh] Translate Savepoints page into Chinese
klion26 commented on a change in pull request #8300: [FLINK-11638][docs-zh]
Translate Savepoints page into Chinese
URL: https://github.com/apache/flink/pull/8300#discussion_r279631660
##
File path: docs/ops/state/savepoints.zh.md
##
@@ -25,32 +25,23 @@ under the License.
* toc
{:toc}
-## What is a Savepoint? How is a Savepoint different from a Checkpoint?
+## 什么是 Savepoint ？ Savepoint 与 Checkpoint 有什么不同？
-A Savepoint is a consistent image of the execution state of a streaming job,
created via Flink's [checkpointing mechanism]({{ site.baseurl
}}/internals/stream_checkpointing.html). You can use Savepoints to
stop-and-resume, fork,
-or update your Flink jobs. Savepoints consist of two parts: a directory with
(typically large) binary files on stable storage (e.g. HDFS, S3, ...) and a
(relatively small) meta data file. The files on stable storage represent the
net data of the job's execution state
-image. The meta data file of a Savepoint contains (primarily) pointers to all
files on stable storage that are part of the Savepoint, in form of absolute
paths.
+Savepoint 是依据 Flink [checkpointing 机制]({{ site.baseurl
}}/internals/stream_checkpointing.html)所创建的流作业执行状态的一致镜像。 你可以使用 Savepoint 进行
Flink 作业的停止与重启、fork或者更新。 Savepoint 由两部分组成：具有稳定存储（例如 HDFS，S3，...）上的（通常是大的）二进制文件
--> 稳定存储（例如 HDFS、S3等）上包含二进制文件的目录（通常很大）和（相对较小的）元数据文件。 稳定存储上的文件表示作业执行状态的数据镜像。
Savepoint 的元数据文件以（绝对路径）的形式包含（主要）指向作为 Savepoint 一部分的稳定存储上的所有文件的指针。
-Attention: In order to allow upgrades between programs and
Flink versions, it is important to check out the following section about assigning IDs to your operators.
+注意: 为了允许程序和 Flink 版本之间的升级，请务必查看以下有关分配算子 ID 的部分 。
+从概念上讲， Flink 的 Savepoint 与 Checkpoint 的不同之处类似于传统数据库中的备份与恢复日志之间的差异。
Checkpoint的主要目的是为意外失败的作为提供恢复机制。 Checkpoint 的生命周期由Flink管理，即 Flink 创建，拥有和发布
Checkpoint - 无需用户交互。 作为一种恢复和定期触发的方法，Checkpoint 实现有两个设计目标：i）轻量级创建和 ii）尽可能快地恢复。
针对这些目标的优化可以利用某些属性，例如， 工作代码在执行尝试之间不会改变。 在用户终止作业后，通常会删除 Checkpoint（除非明确配置为保留的
Checkpoint）。
-Conceptually, Flink's Savepoints are different from Checkpoints in a similar
way that backups are different from recovery logs in traditional database
systems. The primary purpose of Checkpoints is to provide a recovery mechanism
in case of
-unexpected job failures. A Checkpoint's lifecycle is managed by Flink, i.e. a
Checkpoint is created, owned, and released by Flink - without user interaction.
As a method of recovery and being periodically triggered, two main
-design goals for the Checkpoint implementation are i) being as lightweight to
create and ii) being as fast to restore from as possible. Optimizations towards
those goals can exploit certain properties, e.g. that the job code
-doesn't change between the execution attempts. Checkpoints are usually dropped
after the job was terminated by the user (except if explicitly configured as
retained Checkpoints).
+ 与此相反、Savepoint 由用户创建，拥有和删除。 他们的用例是计划的，手动备份和恢复。 例如，这可能是你的Flink
版本的更新，更改你的工作图，改变并行性，分配第二个工作，如红色/蓝色部署，等等。 当然，Savepoint 必须在终止工作后继续存在。
从概念上讲，Savepoint 的生成，恢复和关注成本可能更高一些
Review comment:
`这可能是你的Flink 版本的更新，更改你的工作图，改变并行性，分配第二个工作，如红色/蓝色部署` -> `升级 Flink
版本，调整用户逻辑，改变并行都，以及进行红蓝部署等`
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