wuchong commented on a change in pull request #16852:
URL: https://github.com/apache/flink/pull/16852#discussion_r698426348
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File path: docs/content.zh/docs/dev/datastream/overview.md
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@@ -209,46 +159,30 @@ print()
{{< /tab >}}
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-Once you specified the complete program you need to **trigger the program
-execution** by calling `execute()` on the `StreamExecutionEnvironment`.
-Depending on the type of the `ExecutionEnvironment` the execution will be
-triggered on your local machine or submit your program for execution on a
-cluster.
+一旦指定了完整的程序，需要调用 `StreamExecutionEnvironment` 的 `execute()` 方法来**触发程序执行**。根据
`ExecutionEnvironment` 的类型，执行会在你的本地机器上触发，或将你的程序提交到某个集群上执行。
-The `execute()` method will wait for the job to finish and then return a
-`JobExecutionResult`, this contains execution times and accumulator results.
+`execute()` 方法将等待作业完成，然后返回一个 `JobExecutionResult` ，其中包含执行时间和累加器结果。
-If you don't want to wait for the job to finish, you can trigger asynchronous
-job execution by calling `executeAsync()` on the `StreamExecutionEnvironment`.
-It will return a `JobClient` with which you can communicate with the job you
-just submitted. For instance, here is how to implement the semantics of
-`execute()` by using `executeAsync()`.
+如果不想等待作业完成，可以通过调用 `StreamExecutionEnvironment` 的 `executeAsync()`
方法来触发作业异步执行。它会返回一个 `JobClient` ，你可以通过它与刚刚提交的作业进行通信。如下是使用 `executeAsync()` 实现
`execute()` 语义的示例。
```java
final JobClient jobClient = env.executeAsync();
final JobExecutionResult jobExecutionResult =
jobClient.getJobExecutionResult().get();
```
-That last part about program execution is crucial to understanding when and how
-Flink operations are executed. All Flink programs are executed lazily: When the
-program's main method is executed, the data loading and transformations do not
-happen directly. Rather, each operation is created and added to a dataflow
-graph. The operations are actually executed when the execution is explicitly
-triggered by an `execute()` call on the execution environment. Whether the
-program is executed locally or on a cluster depends on the type of execution
-environment
+关于程序执行的最后一部分对于理解何时以及如何执行 Flink 算子是至关重要的。所有 Flink 程序都是惰性执行的：当程序的 main
方法被执行时，数据加载和转换不会直接发生。相反，每个算子都被创建并添加到 dataflow 形成的有向图。当执行被执行环境的 `execute()`
方法显示地触发时，这些算子才会真正执行。程序是在本地执行还是在集群上执行取决于执行环境的类型。
-The lazy evaluation lets you construct sophisticated programs that Flink
-executes as one holistically planned unit.
+惰性计算让你构建复杂的程序，Flink 将其作为一个整体规划的单元来执行。
Review comment:
延迟计算 也 ok。
咱术语表中有建议这个翻译：https://cwiki.apache.org/confluence/display/FLINK/Flink+Translation+Specifications
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