wuchong commented on a change in pull request #9784: [FLINK-13485]
[chinese-translation] Translate "Table API Example Walkthrough" page into
Chinese
URL: https://github.com/apache/flink/pull/9784#discussion_r336824601
##########
File path: docs/getting-started/walkthroughs/table_api.zh.md
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@@ -299,11 +297,11 @@ This query consumes all records from the `transactions`
table, calculates the re
> 2, 2019-01-01 04:00:00.0, $760.76
{% endhighlight %}
-## Adding Windows
+## 添加窗口
-Grouping data based on time is a typical operation in data processing,
especially when working with infinite streams.
-A grouping based on time is called a [window]({{ site.baseurl }}
/dev/stream/operators/windows.html) and Flink offers flexible windowing
semantics.
-The most basic type of window is called a `Tumble` window, which has a fixed
size and whose buckets do not overlap.
+根据时间进行分组在数据处理中是一种很常见的方式，特别是在处理无限的数据流时。
+基于时间的分组称为[窗口]({{ site.baseurl }}/zh/dev/stream/operators/windows.html) ，Flink
提供了灵活的窗口语义。
+其中最基础的是 `滚动窗口`，它具有固定大小且窗口之间不重叠。
Review comment:
```suggestion
其中最基础的是 `Tumble` window （滚动窗口），它具有固定大小且窗口之间不重叠。
```
Tumble 这里是更多的是指 代码中的 `Tumble`，所以不翻译。
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