YngwieWang commented on a change in pull request #9350: [FLINK-13485]
[chinese-translation] Translate "Table API Example Walkthrough" page into
Chinese
URL: https://github.com/apache/flink/pull/9350#discussion_r310369077
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File path: docs/getting-started/walkthroughs/table_api.zh.md
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@@ -352,13 +356,13 @@ Running the updated query will produce identical results
as before.
> 2, 2019-01-01 04:00:00.0, $760.76
{% endhighlight %}
-## Once More, With Streaming!
+## 通过流的方式再来一次！
-Because Flink's Table API offers consistent syntax and semantics for both
batch and streaming, migrating from one to the other requires just two steps.
+因为Flink的Table API为批和流提供了相同的语法和语义，从一种方式迁移到另一种方式只需要两步。
-The first step is to replace the batch `ExecutionEnvironment` with its
streaming counterpart, `StreamExecutionEnvironment`, which creates a continuous
streaming Job.
-It includes stream-specific configurations, such as the time characteristic,
which when set to [event time]({{ site.baseurl }}/dev/event_time.html)
guarantees consistent results even when faced with out-of-order events or a Job
failure.
-This is what will be used by your `Tumble` window when grouping records.
+第一步就是把批环境使用的 `ExecutionEnvironment` 替换成它在流环境中对应的
`StreamExecutionEnvironment`。`StreamExecutionEnvironment`可以创建一个连续不断的流任务。
Review comment:
```suggestion
第一步是把批处理的 `ExecutionEnvironment` 替换成流处理对应的
`StreamExecutionEnvironment`，后者创建连续的流作业。
```
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