liboshuai01 commented on code in PR #25624:
URL: https://github.com/apache/flink/pull/25624#discussion_r1838350358
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docs/content.zh/docs/dev/datastream/operators/process_function.md:
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@@ -26,68 +26,61 @@ under the License.
# Process Function
-## The ProcessFunction
+## ProcessFunction 简介
-The `ProcessFunction` is a low-level stream processing operation, giving
access to the basic building blocks of
-all (acyclic) streaming applications:
+`ProcessFunction` 是一种低级别的流处理操作，基于它用户可以访问（无环）流应用程序的所有基本构建块：
- - events (stream elements)
- - state (fault-tolerant, consistent, only on keyed stream)
- - timers (event time and processing time, only on keyed stream)
+ - 事件（流元素）
+ - 状态（容错，一致性，仅在 keyed stream 上）
+ - 定时器（事件时间和处理时间，仅在 keyed stream 上）
-The `ProcessFunction` can be thought of as a `FlatMapFunction` with access to
keyed state and timers. It handles events
-by being invoked for each event received in the input stream(s).
+可以将 `ProcessFunction` 视为一种可以访问 keyed state 和定时器的 `FlatMapFunction`。Flink
为收到的输入流中的每个事件都调用该函数来进行处理。
-For fault-tolerant state, the `ProcessFunction` gives access to Flink's [keyed
state]({{< ref "docs/dev/datastream/fault-tolerance/state" >}}), accessible via
the
-`RuntimeContext`, similar to the way other stateful functions can access keyed
state.
+对于容错，与其它有状态的函数类似，`ProcessFunction` 可以通过 `RuntimeContext` 访问 Flink 的 [keyed
state]({{< ref "docs/dev/datastream/fault-tolerance/state" >}})。
-The timers allow applications to react to changes in processing time and in
[event time]({{< ref "docs/concepts/time" >}}).
-Every call to the function `processElement(...)` gets a `Context` object which
gives access to the element's
-event time timestamp, and to the *TimerService*. The `TimerService` can be
used to register callbacks for future
-event-/processing-time instants. With event-time timers, the `onTimer(...)`
method is called when the current watermark is advanced up to or beyond the
timestamp of the timer, while with processing-time timers, `onTimer(...)` is
called when wall clock time reaches the specified time. During that call, all
states are again scoped to the key with which the timer was created, allowing
-timers to manipulate keyed state.
+定时器允许应用程序对处理时间和 [事件时间]({{< ref "docs/concepts/time" >}}) 中的更改做出反应。
+每次调用 `processElement(...)` 时参数中都会提供一个 `Context` 对象，该对象可以访问元素的事件时间戳和
*TimerService*。
+`TimerService` 可用于为将来特定的事件时间/处理时间注册回调。
+特定事件时间的 `onTimer(...)` 回调函数会在当前对齐的 watermark 超过所注册的时间戳时调用。
+特定处理时间的 `onTimer(...)` 回调函数则会在系统物理时间超过所注册的时间戳时调用。
+在该调用期间，所有状态会被再次绑定到创建定时器时的键上，从而允许定时器操作与之对应的 keyed state。
{{< hint info >}}
-If you want to access keyed state and timers you have
-to apply the `ProcessFunction` on a keyed stream:
+如果想要访问 keyed state 和定时器，需要在
+keyed stream 上使用 `ProcessFunction`。
{{< /hint >}}
```java
stream.keyBy(...).process(new MyProcessFunction());
```
-## Low-level Joins
+## 低级别 Join
-To realize low-level operations on two inputs, applications can use
`CoProcessFunction` or `KeyedCoProcessFunction`. This
-function is bound to two different inputs and gets individual calls to
`processElement1(...)` and
-`processElement2(...)` for records from the two different inputs.
+为了在两个输入上实现低级别操作，应用程序可以使用 `CoProcessFunction` 或 `KeyedCoProcessFunction`。
+这些函数绑定两个不同的输入，从两个不同的输入中获取元素并分别调用
+`processElement1(...)` 和 `processElement2(...)` 进行处理。
-Implementing a low level join typically follows this pattern:
+实现低级别 join 一般需要遵循以下模式：
- - Create a state object for one input (or both)
- - Update the state upon receiving elements from its input
- - Upon receiving elements from the other input, probe the state and produce
the joined result
+ - 为一个输入（或两者）创建状态对象。
+ - 从某个输入接收元素时更新状态。
+ - 从另一个输入接收元素时，查询状态并生成 join 结果。
-For example, you might be joining customer data to financial trades,
-while keeping state for the customer data. If you care about having
-complete and deterministic joins in the face of out-of-order events,
-you can use a timer to evaluate and emit the join for a trade when the
-watermark for the customer data stream has passed the time of that
-trade.
+例如，你可能会将客户数据与金融交易进行 join，同时想要保留客户数据的状态。如果你希望即使在出现乱序事件时仍然可以得到完整且确定的 join
结果，你可以通过注册一个定时器在客户数据流的 watermark 已经超过当前这条 finance trade 记录时计算和发送 join 结果。
Review Comment:
是的，已采纳修改。
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