wuchong commented on a change in pull request #9606: [FLINK-13677][docs-zh]
Translate "Monitoring Back Pressure" page into Chinese
URL: https://github.com/apache/flink/pull/9606#discussion_r322254995
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File path: docs/monitoring/back_pressure.zh.md
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@@ -22,59 +22,62 @@ specific language governing permissions and limitations
under the License.
-->
-Flink's web interface provides a tab to monitor the back pressure behaviour of
running jobs.
+Flink Web 界面提供了一个选项卡来监控正在运行 Job 的反压行为。
* ToC
{:toc}
-## Back Pressure
+## 反压
-If you see a **back pressure warning** (e.g. `High`) for a task, this means
that it is producing data faster than the downstream operators can consume.
Records in your job flow downstream (e.g. from sources to sinks) and back
pressure is propagated in the opposite direction, up the stream.
+如果你看到一个 Task 发生 **反压警告**（例如： `High`），意味着它生产数据的速率比下游 Task 消费数据的速率要快。
+在工作流中数据记录是从上游向下游流动的（例如：从 Sources 到 Sinks）。反压沿着相反的方向传播，沿着数据流向上游传播。
-Take a simple `Source -> Sink` job as an example. If you see a warning for
`Source`, this means that `Sink` is consuming data slower than `Source` is
producing. `Sink` is back pressuring the upstream operator `Source`.
+以一个简单的 `Source -> Sink` Job 为例。如果看到 `Source` 发生了警告，意味着 `Sink` 消费数据的速率比
`Source` 生产数据的速率要慢。
+`Sink` 正在向上游的 `Source` 算子产生反压。
-## Sampling Threads
+## 采样线程
-Back pressure monitoring works by repeatedly taking stack trace samples of
your running tasks. The JobManager triggers repeated calls to
`Thread.getStackTrace()` for the tasks of your job.
+通过不断对每个 Task 的 stack trace 采样来进行反压监控。JobManager 会触发对 Task
`Thread.getStackTrace()` 的重复调用。
<img src="{{ site.baseurl }}/fig/back_pressure_sampling.png"
class="img-responsive">
<!--
https://docs.google.com/drawings/d/1_YDYGdUwGUck5zeLxJ5Z5jqhpMzqRz70JxKnrrJUltA/edit?usp=sharing
-->
-If the samples show that a task Thread is stuck in a certain internal method
call (requesting buffers from the network stack), this indicates that there is
back pressure for the task.
+如果样本显示 Task 线程卡在某个内部方法调用中（例如：从网络堆栈请求缓冲区），则表示这个 Task 存在反压。
-By default, the job manager triggers 100 stack traces every 50ms for each task
in order to determine back pressure. The ratio you see in the web interface
tells you how many of these stack traces were stuck in the internal method
call, e.g. `0.01` indicates that only 1 in 100 was stuck in that method.
+默认情况下，JobManager 会触发 100 次 stack trace 采样，每次间隔 50ms 来确定反压。
+你在 Web 界面看到的比率表示在内部方法调用中有多少 stack trace 被卡住，例如: `0.01` 表示在该方法中 100 个只有 1 个被卡住了。
-- **OK**: 0 <= Ratio <= 0.10
-- **LOW**: 0.10 < Ratio <= 0.5
-- **HIGH**: 0.5 < Ratio <= 1
+- **OK**: 0 <= 比例 <= 0.10
+- **LOW**: 0.10 < 比例 <= 0.5
+- **HIGH**: 0.5 < 比例 <= 1
-In order to not overload the task managers with stack trace samples, the web
interface refreshes samples only after 60 seconds.
+为了不因为 stack trace 导致 TaskManager 产生负载，Web 界面仅在 60 秒后重新采样。
-## Configuration
+## 配置参数
-You can configure the number of samples for the job manager with the following
configuration keys:
+你可以使用以下键来配置 JobManager 的样本数：
-- `web.backpressure.refresh-interval`: Time after which available stats are
deprecated and need to be refreshed (DEFAULT: 60000, 1 min).
-- `web.backpressure.num-samples`: Number of stack trace samples to take to
determine back pressure (DEFAULT: 100).
-- `web.backpressure.delay-between-samples`: Delay between stack trace samples
to determine back pressure (DEFAULT: 50, 50 ms).
+- `web.backpressure.refresh-interval`: 有效统计被废弃并重新进行采样的时间 (默认: 60000, 1 min)。
+- `web.backpressure.num-samples`: 用于确定反压的 stack trace 样本数 (默认: 100)。
+- `web.backpressure.delay-between-samples`: 用于确定反压的 stack trace 采样间隔时间 (默认:
50, 50 ms)。
-## Example
+## 案例
Review comment:
```suggestion
## 示例
```
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