authuir commented on a change in pull request #12420:
URL: https://github.com/apache/flink/pull/12420#discussion_r458828105
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File path: docs/dev/table/streaming/joins.zh.md
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@@ -140,26 +138,21 @@ FROM
WHERE r.currency = o.currency
{% endhighlight %}
-Each record from the probe side will be joined with the version of the build
side table at the time of the correlated time attribute of the probe side
record.
-In order to support updates (overwrites) of previous values on the build side
table, the table must define a primary key.
+探针侧的每条记录都将与构建侧的表执行 Join 运算，构建侧的表中与探针侧对应时间属性的记录将参与运算。为了支持更新（包括覆盖）构建侧的表，该表必须定义主键。
-In our example, each record from `Orders` will be joined with the version of
`Rates` at time `o.rowtime`. The `currency` field has been defined as the
primary key of `Rates` before and is used to connect both tables in our
example. If the query were using a processing-time notion, a newly appended
order would always be joined with the most recent version of `Rates` when
executing the operation.
+在示例中，`Orders` 表中的每一条记录都与时间点 `o.rowtime` 的 `Rates` 进行 Join 运算。`currency`
字段已被定义为 `Rates` 表的主键，在示例中该字段也被用于连接两个表。如果该查询采用的是处理时间，则在执行时新增的订单将始终与最新的 `Rates`
执行 Join。
-In contrast to [regular joins](#regular-joins), this means that if there is a
new record on the build side, it will not affect the previous results of the
join.
-This again allows Flink to limit the number of elements that must be kept in
the state.
+与[常规 Join](#regular-joins) 相反，时态表函数 Join 意味着如果在构建侧新增一行记录将不会影响之前的结果。这同时使得 Flink
能够限制必须保存在 state 中的元素数量（因为不再需要保存之前的状态）。
-Compared to [interval joins](#interval-joins), temporal table joins do not
define a time window within which bounds the records will be joined.
-Records from the probe side are always joined with the build side's version at
the time specified by the time attribute. Thus, records on the build side might
be arbitrarily old.
-As time passes, the previous and no longer needed versions of the record (for
the given primary key) will be removed from the state.
+与[时间区间 Join](#interval-joins) 相比，时态表 Join 没有定义限制了每次参与 Join
运算的元素的时间范围。探针侧的记录总是会和构建侧中对应特定时间属性的数据进行 Join
操作。因而在构建侧的记录可以是任意时间之前的。随着时间流动，之前产生的和不再需要的给定 primary key 所对应的记录将从 state 中移除。
-Such behaviour makes a temporal table join a good candidate to express stream
enrichment in relational terms.
+这种做法让时态表 Join 成为一个很好的用于表达不同流之间关联的方法。
-### Usage
+### 用法
Review comment:
Done
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