authuir commented on a change in pull request #12420:
URL: https://github.com/apache/flink/pull/12420#discussion_r444591256
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File path: docs/dev/table/streaming/joins.zh.md
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@@ -22,37 +22,35 @@ specific language governing permissions and limitations
under the License.
-->
-Joins are a common and well-understood operation in batch data processing to
connect the rows of two relations. However, the semantics of joins on [dynamic
tables](dynamic_tables.html) are much less obvious or even confusing.
+Join 在批数据处理中是比较常见且广为人知的运算，一般用于连接两张关系表。然而在[动态表](dynamic_tables.html)中 Join
的语义会更难以理解甚至让人困惑。
-Because of that, there are a couple of ways to actually perform a join using
either Table API or SQL.
+因而，Flink 提供了几种基于 Table API 和 SQL 的 Join 方法。
-For more information regarding the syntax, please check the join sections in
[Table API](../tableApi.html#joins) and [SQL]({{ site.baseurl
}}/dev/table/sql/queries.html#joins).
+欲获取更多关于 Join 语法的细节，请参考 [Table API](../tableApi.html#joins) 和 [SQL]({{
site.baseurl }}/dev/table/sql/queries.html#joins) 中的 Join 章节。
* This will be replaced by the TOC
{:toc}
-Regular Joins
+常规 Join
-------------
-Regular joins are the most generic type of join in which any new records or
changes to either side of the join input are visible and are affecting the
whole join result.
-For example, if there is a new record on the left side, it will be joined with
all of the previous and future records on the right side.
+常规 Join 是最常用的 Join 用法。在常规 Join 中，任何新记录或对 Join 两侧的表的任何更改都是可见的，并会影响最终整个 Join
的结果。例如，如果 Join 左侧插入了一条新的记录，那么它将会与 Join 右侧过去与将来的所有记录一起合并查询。
{% highlight sql %}
SELECT * FROM Orders
INNER JOIN Product
ON Orders.productId = Product.id
{% endhighlight %}
-These semantics allow for any kind of updating (insert, update, delete) input
tables.
+上述语意允许对输入表进行任意类型的更新操作（insert, update, delete）。
-However, this operation has an important implication: it requires to keep both
sides of the join input in Flink's state forever.
-Thus, the resource usage will grow indefinitely as well, if one or both input
tables are continuously growing.
+然而，常规 Join 隐含了一个重要的前提：即它需要在 Flink 的状态中永久保存 Join 两侧的数据。
+因而，如果 Join 操作中的一方或双方输入表持续增长的话，资源消耗也将会随之无限增长。
-Time-windowed Joins
+时间窗口 Join
Review comment:
https://github.com/apache/flink/blob/b6e2f9fb178649c305eb0881be57a46f9ce9911a/docs/dev/table/sql/queries.zh.md
由于 `Time-windowed` 已被重命名为 `Interval
Joins`，参考[此处](https://github.com/apache/flink/blob/b6e2f9fb178649c305eb0881be57a46f9ce9911a/docs/dev/table/sql/queries.zh.md)的翻译为“时间区间
Join”
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