yljee commented on a change in pull request #16316:
URL: https://github.com/apache/flink/pull/16316#discussion_r666151321
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File path: docs/content.zh/docs/dev/table/tableApi.md
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@@ -28,25 +28,24 @@ under the License.
# Table API
-The Table API is a unified, relational API for stream and batch processing.
Table API queries can be run on batch or streaming input without modifications.
The Table API is a super set of the SQL language and is specially designed for
working with Apache Flink. The Table API is a language-integrated API for
Scala, Java and Python. Instead of specifying queries as String values as
common with SQL, Table API queries are defined in a language-embedded style in
Java, Scala or Python with IDE support like autocompletion and syntax
validation.
+Table API 是批处理和流处理的统一的关系 API。Table API 的查询不需要修改代码就可以采用批输入或流输入来运行。Table API 是
SQL 语言的超集，并且是针对Apache Flink 专门设计的。Table API 集成了 Scala, Java 和 Python 语言的
API。Table API 的查询是使用 Java, Scala 或 Python 语言嵌入的风格定义的，有诸如自动补全和语法校验的 IDE
支持，而不是像普通 SQL 一样使用字符串类型的值来指定查询。
-The Table API shares many concepts and parts of its API with Flink's SQL
integration. Have a look at the [Common Concepts & API]({{< ref
"docs/dev/table/common" >}}) to learn how to register tables or to create a
`Table` object. The [Streaming Concepts]({{< ref
"docs/dev/table/concepts/overview" >}}) pages discuss streaming specific
concepts such as dynamic tables and time attributes.
+Table API 和 Flink SQL 共享许多概念以及部分集成的 API。通过查看 [公共概念 & API]({{< ref
"docs/dev/table/common" >}}) 来学习如何注册表或如何创建一个表对象。 [流概念]({{< ref
"docs/dev/table/concepts/overview" >}})页面讨论了诸如动态表和时间属性等流特有的概念。
Review comment:
好的，我修改一下
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File path: docs/content.zh/docs/dev/table/tableApi.md
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@@ -1016,8 +1018,8 @@ result = joined_table.select(joined_table.a,
joined_table.b, joined_table.e, joi
{{< label "Batch" >}} {{< label "Streaming" >}}
-Joins a table with the results of a table function. Each row of the left
(outer) table is joined with all rows produced by the corresponding call of the
table function.
-A row of the left (outer) table is dropped, if its table function call returns
an empty result.
+join表和表函数的结果。左（外部）表的每一行都会join表函数的相应调用产生的所有行。
Review comment:
好的，我修改一下
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File path: docs/content.zh/docs/dev/table/tableApi.md
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@@ -1345,7 +1347,7 @@ left.minusAll(right)
{{< label Batch >}} {{< label Streaming >}}
-Similar to a SQL `IN` clause. In returns true if an expression exists in a
given table sub-query. The sub-query table must consist of one column. This
column must have the same data type as the expression.
+和 SQL `IN` 子句类似。如果在给定表的子查询中存在包含in的表达式，则返回true。子查询表必须由一列组成。这个列必须与表达式具有相同的数据类型。
Review comment:
好的，我修改一下
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File path: docs/content.zh/docs/dev/table/tableApi.md
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@@ -2155,7 +2158,7 @@ The row-based operations generate outputs with multiple
columns.
{{< tabs "map" >}}
{{< tab "Java" >}}
-Performs a map operation with a user-defined scalar function or built-in
scalar function. The output will be flattened if the output type is a composite
type.
+使用用户定义的标量函数或内置标量函数执行map操作。如果输出类型是复合类型，则输出将被展平。
Review comment:
好的，我修改一下
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File path: docs/content.zh/docs/dev/table/tableApi.md
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@@ -2197,7 +2200,7 @@ val table = input
{{< /tab >}}
{{< tab "Python" >}}
-Performs a map operation with a python [general scalar function]({{< ref
"docs/dev/python/table/udfs/python_udfs" >}}#scalar-functions) or [vectorized
scalar function]({{< ref "docs/dev/python/table/udfs/vectorized_python_udfs"
>}}#vectorized-scalar-functions). The output will be flattened if the output
type is a composite type.
+使用 python 的[一般标量函数]({{< ref "docs/dev/python/table/udfs/python_udfs"
>}}#scalar-functions)或[向量化标量函数]({{< ref
"docs/dev/python/table/udfs/vectorized_python_udfs"
>}}#vectorized-scalar-functions)执行map操作。如果输出类型是复合类型，则输出将被展平。
Review comment:
好的，我修改一下
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