ZhijieYang commented on a change in pull request #16348:
URL: https://github.com/apache/flink/pull/16348#discussion_r664195807
##########
File path: docs/content.zh/docs/dev/table/functions/systemFunctions.md
##########
@@ -24,161 +24,161 @@ specific language governing permissions and limitations
under the License.
-->
-# System (Built-in) Functions
+# 系统（内置）函数
-Flink Table API & SQL provides users with a set of built-in functions for data
transformations. This page gives a brief overview of them.
-If a function that you need is not supported yet, you can implement a
[user-defined function]({{< ref "docs/dev/table/functions/udfs" >}}).
-If you think that the function is general enough, please <a
href="https://issues.apache.org/jira/secure/CreateIssue!default.jspa";>open a
Jira issue</a> for it with a detailed description.
+Flink Table API & SQL 为用户提供了一组内置的数据转换函数。本页简要介绍了它们。如果您需要的功能尚不支持，您可以实现
+[用户自定义功能]({{< ref "docs/dev/table/functions/udfs" >}})。如果你觉得这个功能够通用， 请
+<a href="https://issues.apache.org/jira/secure/CreateIssue!default.jspa";>创建一个
Jira issue</a>并详细
+说明。
-Scalar Functions
+标量函数
----------------
-The scalar functions take zero, one or more values as the input and return a
single value as the result.
+标量函数将零、一个或多个值作为输入并返回单个值作为结果。
-### Comparison Functions
+### 比较函数
-{{< sql_functions "comparison" >}}
+{{< sql_functions_zh "comparison" >}}
-### Logical Functions
+### 逻辑函数
-{{< sql_functions "logical" >}}
+{{< sql_functions_zh "logical" >}}
-### Arithmetic Functions
+### 算术函数
-{{< sql_functions "arithmetic" >}}
+{{< sql_functions_zh "arithmetic" >}}
-### String Functions
+### 字符串函数
-{{< sql_functions "string" >}}
+{{< sql_functions_zh "string" >}}
-### Temporal Functions
+### 时间函数
-{{< sql_functions "temporal" >}}
+{{< sql_functions_zh "temporal" >}}
-### Conditional Functions
+### 条件函数
-{{< sql_functions "conditional" >}}
+{{< sql_functions_zh "conditional" >}}
-### Type Conversion Functions
+### 类型转换函数
-{{< sql_functions "conversion" >}}
+{{< sql_functions_zh "conversion" >}}
-### Collection Functions
+### 集合函数
-{{< sql_functions "collection" >}}
+{{< sql_functions_zh "collection" >}}
-### Value Construction Functions
+### 构建值函数
-{{< sql_functions "valueconstruction" >}}
+{{< sql_functions_zh "valueconstruction" >}}
-### Value Access Functions
+### 获取值函数
-{{< sql_functions "valueaccess" >}}
+{{< sql_functions_zh "valueaccess" >}}
-### Grouping Functions
+### 分组函数
-{{< sql_functions "grouping" >}}
+{{< sql_functions_zh "grouping" >}}
-### Hash Functions
+### 哈希函数
-{{< sql_functions "hashfunctions" >}}
+{{< sql_functions_zh "hashfunctions" >}}
-### Auxiliary Functions
+### 辅助功能
-{{< sql_functions "auxilary" >}}
+{{< sql_functions_zh "auxilary" >}}
-Aggregate Functions
+聚合函数
-------------------
-The aggregate functions take an expression across all the rows as the input
and return a single aggregated value as the result.
+聚合函数将所有的行作为输入，并返回单个聚合值作为结果。
-{{< sql_functions "aggregate" >}}
+{{< sql_functions_zh "aggregate" >}}
-Time Interval and Point Unit Specifiers
+时间间隔和点单位说明符
---------------------------------------
-The following table lists specifiers for time interval and time point units.
-
-For Table API, please use `_` for spaces (e.g., `DAY_TO_HOUR`).
-
-| Time Interval Unit | Time Point Unit |
-| :----------------------- | :----------------------------- |
-| `MILLENIUM` _(SQL-only)_ | |
-| `CENTURY` _(SQL-only)_ | |
-| `YEAR` | `YEAR` |
-| `YEAR TO MONTH` | |
-| `QUARTER` | `QUARTER` |
-| `MONTH` | `MONTH` |
-| `WEEK` | `WEEK` |
-| `DAY` | `DAY` |
-| `DAY TO HOUR` | |
-| `DAY TO MINUTE` | |
-| `DAY TO SECOND` | |
-| `HOUR` | `HOUR` |
-| `HOUR TO MINUTE` | |
-| `HOUR TO SECOND` | |
-| `MINUTE` | `MINUTE` |
-| `MINUTE TO SECOND` | |
-| `SECOND` | `SECOND` |
-| | `MILLISECOND` |
-| | `MICROSECOND` |
-| `DOY` _(SQL-only)_ | |
-| `DOW` _(SQL-only)_ | |
-| | `SQL_TSI_YEAR` _(SQL-only)_ |
-| | `SQL_TSI_QUARTER` _(SQL-only)_ |
-| | `SQL_TSI_MONTH` _(SQL-only)_ |
-| | `SQL_TSI_WEEK` _(SQL-only)_ |
-| | `SQL_TSI_DAY` _(SQL-only)_ |
-| | `SQL_TSI_HOUR` _(SQL-only)_ |
-| | `SQL_TSI_MINUTE` _(SQL-only)_ |
-| | `SQL_TSI_SECOND ` _(SQL-only)_ |
+下表列出了时间间隔和时间点单位的说明符。
+
+对于 Table API，请使用 `_` 代替空格（例如 `DAY_TO_HOUR`）。
+
+| 时间间隔单位 | 时间点单位 |
+| :------------------------ | :------------------------------ |
+| `MILLENIUM` _（仅适用SQL）_ | |
+| `CENTURY` _（仅适用SQL）_ | |
+| `YEAR` | `YEAR` |
+| `YEAR TO MONTH` | |
+| `QUARTER` | `QUARTER` |
+| `MONTH` | `MONTH` |
+| `WEEK` | `WEEK` |
+| `DAY` | `DAY` |
+| `DAY TO HOUR` | |
+| `DAY TO MINUTE` | |
+| `DAY TO SECOND` | |
+| `HOUR` | `HOUR` |
+| `HOUR TO MINUTE` | |
+| `HOUR TO SECOND` | |
+| `MINUTE` | `MINUTE` |
+| `MINUTE TO SECOND` | |
+| `SECOND` | `SECOND` |
+| | `MILLISECOND` |
+| | `MICROSECOND` |
+| `DOY` _（仅适用SQL）_ | |
+| `DOW` _（仅适用SQL）_ | |
+| | `SQL_TSI_YEAR` _（仅适用SQL）_ |
+| | `SQL_TSI_QUARTER` _（仅适用SQL）_ |
+| | `SQL_TSI_MONTH` _（仅适用SQL）_ |
+| | `SQL_TSI_WEEK` _（仅适用SQL）_ |
+| | `SQL_TSI_DAY` _（仅适用SQL）_ |
+| | `SQL_TSI_HOUR` _（仅适用SQL）_ |
+| | `SQL_TSI_MINUTE` _（仅适用SQL）_ |
+| | `SQL_TSI_SECOND ` _（仅适用SQL）_ |
{{< top >}}
-Column Functions
+列函数
---------------------------------------
-The column functions are used to select or deselect table columns.
+列函数用于选择或不选表的列。
Review comment:
How about `列函数用于选择或丢弃表的列。` sounds smoothly.
##########
File path: docs/content.zh/docs/dev/table/functions/systemFunctions.md
##########
@@ -24,161 +24,161 @@ specific language governing permissions and limitations
under the License.
-->
-# System (Built-in) Functions
+# 系统（内置）函数
-Flink Table API & SQL provides users with a set of built-in functions for data
transformations. This page gives a brief overview of them.
-If a function that you need is not supported yet, you can implement a
[user-defined function]({{< ref "docs/dev/table/functions/udfs" >}}).
-If you think that the function is general enough, please <a
href="https://issues.apache.org/jira/secure/CreateIssue!default.jspa";>open a
Jira issue</a> for it with a detailed description.
+Flink Table API & SQL 为用户提供了一组内置的数据转换函数。本页简要介绍了它们。如果您需要的功能尚不支持，您可以实现
+[用户自定义功能]({{< ref "docs/dev/table/functions/udfs" >}})。如果你觉得这个功能够通用， 请
Review comment:
there is no doubt that the `function` is translated into `函数`.
but I don't agree that the author wants to express `不够通用`, because only when
the function is general enough you can open a Jira for it.
##########
File path: docs/content.zh/docs/dev/table/functions/systemFunctions.md
##########
@@ -24,161 +24,161 @@ specific language governing permissions and limitations
under the License.
-->
-# System (Built-in) Functions
+# 系统（内置）函数
-Flink Table API & SQL provides users with a set of built-in functions for data
transformations. This page gives a brief overview of them.
-If a function that you need is not supported yet, you can implement a
[user-defined function]({{< ref "docs/dev/table/functions/udfs" >}}).
-If you think that the function is general enough, please <a
href="https://issues.apache.org/jira/secure/CreateIssue!default.jspa";>open a
Jira issue</a> for it with a detailed description.
+Flink Table API & SQL 为用户提供了一组内置的数据转换函数。本页简要介绍了它们。如果您需要的功能尚不支持，您可以实现
+[用户自定义功能]({{< ref "docs/dev/table/functions/udfs" >}})。如果你觉得这个功能够通用， 请
+<a href="https://issues.apache.org/jira/secure/CreateIssue!default.jspa";>创建一个
Jira issue</a>并详细
+说明。
-Scalar Functions
+标量函数
----------------
-The scalar functions take zero, one or more values as the input and return a
single value as the result.
+标量函数将零、一个或多个值作为输入并返回单个值作为结果。
-### Comparison Functions
+### 比较函数
-{{< sql_functions "comparison" >}}
+{{< sql_functions_zh "comparison" >}}
-### Logical Functions
+### 逻辑函数
-{{< sql_functions "logical" >}}
+{{< sql_functions_zh "logical" >}}
-### Arithmetic Functions
+### 算术函数
-{{< sql_functions "arithmetic" >}}
+{{< sql_functions_zh "arithmetic" >}}
-### String Functions
+### 字符串函数
-{{< sql_functions "string" >}}
+{{< sql_functions_zh "string" >}}
-### Temporal Functions
+### 时间函数
-{{< sql_functions "temporal" >}}
+{{< sql_functions_zh "temporal" >}}
-### Conditional Functions
+### 条件函数
-{{< sql_functions "conditional" >}}
+{{< sql_functions_zh "conditional" >}}
-### Type Conversion Functions
+### 类型转换函数
-{{< sql_functions "conversion" >}}
+{{< sql_functions_zh "conversion" >}}
-### Collection Functions
+### 集合函数
-{{< sql_functions "collection" >}}
+{{< sql_functions_zh "collection" >}}
-### Value Construction Functions
+### 构建值函数
-{{< sql_functions "valueconstruction" >}}
+{{< sql_functions_zh "valueconstruction" >}}
-### Value Access Functions
+### 获取值函数
-{{< sql_functions "valueaccess" >}}
+{{< sql_functions_zh "valueaccess" >}}
-### Grouping Functions
+### 分组函数
-{{< sql_functions "grouping" >}}
+{{< sql_functions_zh "grouping" >}}
-### Hash Functions
+### 哈希函数
-{{< sql_functions "hashfunctions" >}}
+{{< sql_functions_zh "hashfunctions" >}}
-### Auxiliary Functions
+### 辅助功能
Review comment:
How about `辅助函数`?
##########
File path: docs/content.zh/docs/dev/table/functions/systemFunctions.md
##########
@@ -24,161 +24,161 @@ specific language governing permissions and limitations
under the License.
-->
-# System (Built-in) Functions
+# 系统（内置）函数
-Flink Table API & SQL provides users with a set of built-in functions for data
transformations. This page gives a brief overview of them.
-If a function that you need is not supported yet, you can implement a
[user-defined function]({{< ref "docs/dev/table/functions/udfs" >}}).
-If you think that the function is general enough, please <a
href="https://issues.apache.org/jira/secure/CreateIssue!default.jspa";>open a
Jira issue</a> for it with a detailed description.
+Flink Table API & SQL 为用户提供了一组内置的数据转换函数。本页简要介绍了它们。如果您需要的功能尚不支持，您可以实现
+[用户自定义功能]({{< ref "docs/dev/table/functions/udfs" >}})。如果你觉得这个功能够通用， 请
+<a href="https://issues.apache.org/jira/secure/CreateIssue!default.jspa";>创建一个
Jira issue</a>并详细
+说明。
-Scalar Functions
+标量函数
----------------
-The scalar functions take zero, one or more values as the input and return a
single value as the result.
+标量函数将零、一个或多个值作为输入并返回单个值作为结果。
-### Comparison Functions
+### 比较函数
-{{< sql_functions "comparison" >}}
+{{< sql_functions_zh "comparison" >}}
-### Logical Functions
+### 逻辑函数
-{{< sql_functions "logical" >}}
+{{< sql_functions_zh "logical" >}}
-### Arithmetic Functions
+### 算术函数
-{{< sql_functions "arithmetic" >}}
+{{< sql_functions_zh "arithmetic" >}}
-### String Functions
+### 字符串函数
-{{< sql_functions "string" >}}
+{{< sql_functions_zh "string" >}}
-### Temporal Functions
+### 时间函数
-{{< sql_functions "temporal" >}}
+{{< sql_functions_zh "temporal" >}}
-### Conditional Functions
+### 条件函数
-{{< sql_functions "conditional" >}}
+{{< sql_functions_zh "conditional" >}}
-### Type Conversion Functions
+### 类型转换函数
-{{< sql_functions "conversion" >}}
+{{< sql_functions_zh "conversion" >}}
-### Collection Functions
+### 集合函数
-{{< sql_functions "collection" >}}
+{{< sql_functions_zh "collection" >}}
-### Value Construction Functions
+### 构建值函数
-{{< sql_functions "valueconstruction" >}}
+{{< sql_functions_zh "valueconstruction" >}}
-### Value Access Functions
+### 获取值函数
-{{< sql_functions "valueaccess" >}}
+{{< sql_functions_zh "valueaccess" >}}
-### Grouping Functions
+### 分组函数
Review comment:
but I don't think `Grouping` is a special word here. If you think it's
necessary I will modify it. @RocMarshal
##########
File path: docs/data/sql_functions_zh.yml
##########
@@ -0,0 +1,820 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements. See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership. The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License. You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied. See the License for the
+# specific language governing permissions and limitations
+# under the License
+
+comparison:
+ - sql: value1 = value2
+ table: value1 === value2
+ description: 如果 value1 等于 value2 返回 `TRUE`；如果 value1 或者 value2 为 NULL 返回
`UNKNOW`。
+ - sql: value1 <> value2
+ table: value1 !== value2
+ description: 如果 value1 不等于 value2 返回 `TRUE`；如果 value1 或 value2 为 NULL 返回
`UNKNOWN`。
+ - sql: value1 > value2
+ table: value1 > value2
+ description: 如果 value1 大于 value2 返回 `TRUE`；如果 value1 或 value2 为 NULL 返回
`UNKNOWN`。
+ - sql: value1 >= value2
+ table: value1 >= value2
+ description: 如果 value1 大于或等于 value2 返回 `TRUE`；如果 value1 或 value2 为 NULL 返回
`UNKNOWN`。
+ - sql: value1 < value2
+ table: value1 < value2
+ description: 如果 value1 小于 value2 返回 `TRUE`；如果 value1 或 value2 为 NULL 返回
`UNKNOWN`。
+ - sql: value1 <= value2
+ table: value1 <= value2
+ description: 如果 value1 小于或等于 value2 返回 `TRUE`；如果 value1 或 value2 为 NULL 返回
`UNKNOWN`。
+ - sql: value IS NULL
+ table: value.isNull
+ description: 如果值为 NULL 返回 `TRUE`。
+ - sql: value IS NOT NULL
+ table: value.isNotNull
+ description: 如果值不为 NULL 返回 `TRUE`。
+ - sql: value1 IS DISTINCT FROM value2
+ description: |
+ A 和 B 的数据类型、值不完全相同返回 `TRUE`。A 和 B 的数据类型、值都相同返回 `FALSE`。将 NULL 视为相同。
+ 例如 `1 IS DISTINCT FROM NULL` 返回 `TRUE`；`NULL IS DISTINCT FROM NULL` 返回
`FALSE`。
+ - sql: value1 IS NOT DISTINCT FROM value2
+ description: |
+ A 和 B 的数据类型、值都相同返回 `TRUE`。A 和 B 的数据类型、值不完全相同则返回 `FALSE`。将 NULL 视为相同。
+ 例如 `1 IS NOT DISTINCT FROM NULL` 返回 `FALSE`；`NULL IS NOT DISTINCT FROM
NULL` 返回 `TRUE`。
+ - sql: value1 BETWEEN [ ASYMMETRIC | SYMMETRIC ] value2 AND value3
+ description: |
+ 默认或使用 ASYMMETRIC 关键字的情况下，如果 value1 大于等于 value2 且小于等于 value3 返回 `TRUE`。
+ 使用 SYMMETRIC 关键字则 value1 在 value2 和 value3 之间返回 `TRUE`。
+ 当 value2 或 value3 为 NULL 时，返回 `FALSE` 或`UNKNOWN`。
+ 例如 `12 BETWEEN 15 AND 12` 返回 `FALSE`；
+ `12 BETWEEN SYMMETRIC 15 AND 12` 返回 `TRUE`；
+ `12 BETWEEN 10 AND NULL` 返回 `UNKNOWN`；
+ `12 BETWEEN NULL AND 10` 返回 `FALSE`；
+ `12 BETWEEN SYMMETRIC NULL AND 12` 返回 `UNKNOWN`。
+ - sql: value1 NOT BETWEEN [ ASYMMETRIC | SYMMETRIC ] value2 AND value3
+ description: |
+ 默认或使用 ASYMMETRIC 关键字的情况下，如果 value1 小于 value2 或大于 value3，则返回 `TRUE`。
+ 使用 SYMMETRIC 关键字则 value1 不在 value2 和 value3 之间返回 `TRUE`。
+ 当 value2 或 value3 为 NULL 时，返回 `TRUE` 或 `UNKNOWN`。
+ 例如 `12 NOT BETWEEN 15 AND 12` 返回 `TRUE`；
+ `12 NOT BETWEEN SYMMETRIC 15 AND 12` 返回 `FALSE`；
+ `12 NOT BETWEEN NULL AND 15` 返回 `UNKNOWN`；
+ `12 NOT BETWEEN 15 AND NULL` 返回 `TRUE`；
+ `12 NOT BETWEEN SYMMETRIC 12 AND NULL` 返回 `UNKNOWN`。
+ - sql: string1 LIKE string2 [ ESCAPE char ]
+ table: string1.like(string2)
+ description: |
+ 如果 string1 匹配 string2 返回 `TRUE`；如果 string1 或 string2 为 NULL 返回 `UNKNOWN`。
+ 如果需要可以定义转义字符。尚不支持转义字符。
+ - sql: string1 NOT LIKE string2 [ ESCAPE char ]
+ description: |
+ 如果 string1 与 string2 不匹配返回 `TRUE`；如果 string1 或 string2 为 NULL 返回
`UNKNOWN`。
+ 如果需要可以定义转义字符。尚不支持转义字符。
+ - sql: string1 SIMILAR TO string2 [ ESCAPE char ]
+ table: string1.similar(string2)
+ description: |
+ 如果 string1 匹配 SQL 正则表达式 string2 返回 `TRUE`；如果 string1 或 string2 为 NULL 返回
+ `UNKNOWN`。如果需要可以定义转义字符。尚不支持转义字符。
+ - sql: string1 NOT SIMILAR TO string2 [ ESCAPE char ]
+ description: |
+ 如果 string1 与 SQL 正则表达式 string2 不匹配返回 `TRUE`；如果 string1 或 string2 为 NULL
返回
+ `UNKNOWN`。如果需要可以定义转义字符。尚不支持转义字符。
+ - sql: value1 IN (value2 [, value3]* )
+ table: value1.in(valu2)
+ description: |
+ 在给定列表（value2、value3、...）中存在 value1 返回 `TRUE`。当列表包含 NULL，如果可以找到 value1 则返回
Review comment:
I will change all the `、` to `，`
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