apache · yiguolei · Apr 29, 2022 · Apr 28, 2022 · Apr 28, 2022 · Apr 28, 2022
diff --git a/docs/.vuepress/sidebar/en.js b/docs/.vuepress/sidebar/en.js
@@ -502,7 +502,7 @@ module.exports = [
           },
           {
             title: "Encryption Functions",
-            directoryPath: "encrypt-dixgest-functions/",
+            directoryPath: "encrypt-digest-functions/",
             initialOpenGroupIndex: -1,
             children: [
               "aes",
@@ -524,7 +524,6 @@ module.exports = [
               "outer-combinator"
             ],
           },
-          "window-function",
           "cast",
           "digital-masking",
         ],

diff --git a/docs/.vuepress/sidebar/zh-CN.js b/docs/.vuepress/sidebar/zh-CN.js
@@ -502,7 +502,7 @@ module.exports = [
           },
           {
             title: "加密和信息摘要函数",
-            directoryPath: "encrypt-dixgest-functions/",
+            directoryPath: "encrypt-digest-functions/",
             initialOpenGroupIndex: -1,
             children: [
               "aes",
@@ -524,7 +524,6 @@ module.exports = [
               "outer-combinator"
             ],
           },
-          "window-function",
           "cast",
           "digital-masking",
         ],

diff --git a/docs/en/get-starting/get-starting.md b/docs/en/get-starting/get-starting.md
@@ -151,7 +151,7 @@ Doris uses the MySQL protocol for communication, and users can connect to the Do
 
 By default, Http protocol is used for WebUI access, and the following format address is entered in the browser to access
 
-```cql
+```
 http://FE_IP:FE_HTTP_PORT(默认8030)
 ```
 
@@ -688,4 +688,4 @@ The current UPDATE statement **only supports** row updates on the Unique model,
 
        ```sql
        DELETE FROM my_table PARTITIONS (p1, p2) WHERE k1 >= 3 AND k2 = "abc";
-       ````
+       ````
diff --git a/docs/en/sql-manual/sql-functions/aggregate-functions/approx_count_distinct.md b/docs/en/sql-manual/sql-functions/aggregate-functions/approx_count_distinct.md
@@ -24,9 +24,9 @@ specific language governing permissions and limitations
 under the License.
 -->
 
-# APPROX_COUNT_DISTINCT
-## Description
-### Syntax
+## APPROX_COUNT_DISTINCT
+### Description
+#### Syntax
 
 `APPROX_COUNT_DISTINCT (expr)`
 
@@ -35,7 +35,7 @@ Returns an approximate aggregation function similar to the result of COUNT (DIST
 
 It combines COUNT and DISTINCT faster and uses fixed-size memory, so less memory can be used for columns with high cardinality.
 
-## example
+### example
 ```
 MySQL > select approx_count_distinct(query_id) from log_statis group by datetime;
 +-----------------+
@@ -44,6 +44,6 @@ MySQL > select approx_count_distinct(query_id) from log_statis group by datetime
 | 17721           |
 +-----------------+
 ```
-## keyword
+### keywords
 
 APPROX_COUNT_DISTINCT
diff --git a/docs/en/sql-manual/sql-functions/aggregate-functions/avg.md b/docs/en/sql-manual/sql-functions/aggregate-functions/avg.md
@@ -25,9 +25,9 @@ under the License.
 -->
 
 
-#AVG
-## Description
-### Syntax
+## AVG
+### Description
+#### Syntax
 
 `AVG([DISTINCT] expr)`
 
@@ -36,7 +36,7 @@ Used to return the average value of the selected field
 
 Optional field DISTINCT parameters can be used to return the weighted average
 
-## example
+### example
 
 ```
 mysql> SELECT datetime, AVG(cost_time) FROM log_statis group by datetime;
@@ -54,6 +54,6 @@ mysql> SELECT datetime, AVG(distinct cost_time) FROM log_statis group by datetim
 +---------------------+---------------------------+
 
 ```
-## keyword
+### keywords
 
 AVG
diff --git a/docs/en/sql-manual/sql-functions/aggregate-functions/bitmap_union.md b/docs/en/sql-manual/sql-functions/aggregate-functions/bitmap_union.md
@@ -25,9 +25,13 @@ under the License.
 -->
 
 
-# BITMAP_UNION
+## BITMAP_UNION
 
-## Create table
+### description
+
+### example
+
+#### Create table
 
 The aggregation model needs to be used when creating the table. The data type is bitmap and the aggregation function is bitmap_union.
 ```
@@ -47,15 +51,15 @@ Note: When the amount of data is large, it is best to create a corresponding rol
 ALTER TABLE pv_bitmap ADD ROLLUP pv (page, user_id);
 ```
 
-## Data Load
+#### Data Load
 
 `TO_BITMAP (expr)`: Convert 0 ~ 18446744073709551615 unsigned bigint to bitmap
 
 `BITMAP_EMPTY ()`: Generate empty bitmap columns, used for insert or import to fill the default value
 
 `BITMAP_HASH (expr)`: Convert any type of column to a bitmap by hashing
 
-### Stream Load
+##### Stream Load
 
 ```
 cat data | curl --location-trusted -u user: passwd -T--H "columns: dt, page, user_id, user_id = to_bitmap (user_id)" http: // host: 8410 / api / test / testDb / _stream_load
@@ -69,7 +73,7 @@ cat data | curl --location-trusted -u user: passwd -T--H "columns: dt, page, use
 cat data | curl --location-trusted -u user: passwd -T--H "columns: dt, page, user_id, user_id = bitmap_empty ()" http: // host: 8410 / api / test / testDb / _stream_load
 ```
 
-### Insert Into
+##### Insert Into
 
 id2's column type is bitmap
 ```
@@ -97,9 +101,9 @@ insert into bitmap_table1 select id, bitmap_hash (id_string) from table;
 ```
 
 
-## Data Query
+#### Data Query
 
-### Syntax
+##### Syntax
 
 
 `BITMAP_UNION (expr)`: Calculate the union of two Bitmaps. The return value is the new Bitmap value.
@@ -112,7 +116,7 @@ insert into bitmap_table1 select id, bitmap_hash (id_string) from table;
 filter_column The cardinality of the intersection of multiple bitmaps of the filter.
 bitmap_column_to_count is a column of type bitmap, filter_column is a column of varying dimensions, and filter_values is a list of dimension values.
 
-### Example
+##### Example
 
 The following SQL uses the pv_bitmap table above as an example:
 
@@ -140,7 +144,6 @@ from pv_bitmap
 where page in ('meituan', 'waimai');
 ```
 
-
-## keyword
+### keywords
 
 BITMAP, BITMAP_COUNT, BITMAP_EMPTY, BITMAP_UNION, BITMAP_UNION_INT, TO_BITMAP, BITMAP_UNION_COUNT, INTERSECT_COUNT
diff --git a/docs/en/sql-manual/sql-functions/aggregate-functions/count.md b/docs/en/sql-manual/sql-functions/aggregate-functions/count.md
@@ -24,16 +24,16 @@ specific language governing permissions and limitations
 under the License.
 -->
 
-# COUNT
-## Description
-### Syntax
+## COUNT
+### Description
+#### Syntax
 
 `COUNT([DISTINCT] expr)`
 
 
 Number of rows used to return the required rows
 
-## example
+### example
 
 ```
 MySQL > select count(*) from log_statis group by datetime;
@@ -57,5 +57,5 @@ MySQL > select count(distinct datetime) from log_statis group by datetime;
 |                       71045   |
 +-------------------------------+
 ```
-## keyword
+### keywords
 COUNT
diff --git a/docs/en/sql-manual/sql-functions/aggregate-functions/group_concat.md b/docs/en/sql-manual/sql-functions/aggregate-functions/group_concat.md
@@ -24,16 +24,16 @@ specific language governing permissions and limitations
 under the License.
 -->
 
-# group_concat
-## description
-### Syntax
+## group_concat
+### description
+#### Syntax
 
 `VARCHAR GROUP_CONCAT(VARCHAR str[, VARCHAR sep])`
 
 
 This function is an aggregation function similar to sum (), and group_concat links multiple rows of results in the result set to a string. The second parameter, sep, is a connection symbol between strings, which can be omitted. This function usually needs to be used with group by statements.
 
-## example
+### example
 
 ```
 mysql> select value from test;
@@ -66,5 +66,5 @@ mysql> select GROUP_CONCAT(value, NULL) from test;
 | NULL                       |
 +----------------------------+
 ```
-## keyword
+### keywords
 GROUP_CONCAT,GROUP,CONCAT
diff --git a/docs/en/sql-manual/sql-functions/aggregate-functions/hll_union_agg.md b/docs/en/sql-manual/sql-functions/aggregate-functions/hll_union_agg.md
@@ -24,9 +24,9 @@ specific language governing permissions and limitations
 under the License.
 -->
 
-# HLL_UNION_AGG
-## description
-### Syntax
+## HLL_UNION_AGG
+### description
+#### Syntax
 
 `HLL_UNION_AGG(hll)`
 
@@ -39,7 +39,7 @@ Based on this, we get an estimate with an error of about 1%. The HLL column is g
 
 When importing, hll_hash function is used to specify which column in data is used to generate HLL column. It is often used to replace count distinct, and to calculate UV quickly in business by combining rollup.
 
-## example
+### example
 ```
 MySQL > select HLL_UNION_AGG(uv_set) from test_uv;;
 +-------------------------+
@@ -48,5 +48,5 @@ THE COURT OF JUSTICE OF THE EUROPEAN COMMUNITIES,
 | 17721                   |
 +-------------------------+
 ```
-## keyword
+### keywords
 HLL_UNION_AGG,HLL,UNION,AGG
diff --git a/docs/en/sql-manual/sql-functions/aggregate-functions/max.md b/docs/en/sql-manual/sql-functions/aggregate-functions/max.md
@@ -24,16 +24,16 @@ specific language governing permissions and limitations
 under the License.
 -->
 
-# MAX
-## description
-### Syntax
+## MAX
+### description
+#### Syntax
 
 `MAX(expr)`
 
 
 Returns the maximum value of an expr expression
 
-## example
+### example
 ```
 MySQL > select max(scan_rows) from log_statis group by datetime;
 +------------------+
@@ -42,5 +42,5 @@ MySQL > select max(scan_rows) from log_statis group by datetime;
 |          4671587 |
 +------------------+
 ```
-## keyword
+### keywords
 MAX
diff --git a/docs/en/sql-manual/sql-functions/aggregate-functions/max_by.md b/docs/en/sql-manual/sql-functions/aggregate-functions/max_by.md
@@ -24,16 +24,16 @@ specific language governing permissions and limitations
 under the License.
 -->
 
-# MAX_BY
-## description
-### Syntax
+## MAX_BY
+### description
+#### Syntax
 
 `MAX_BY(expr1, expr2)`
 
 
 Returns the value of an expr1 associated with the maximum value of expr2 in a group.
 
-## example
+### example
 ```
 MySQL > select * from tbl;
 +------+------+------+------+
@@ -52,5 +52,5 @@ MySQL > select max_by(k1, k4) from tbl;
 |                  0 |
 +--------------------+ 
 ```
-## keyword
+### keywords
 MAX_BY
diff --git a/docs/en/sql-manual/sql-functions/aggregate-functions/min.md b/docs/en/sql-manual/sql-functions/aggregate-functions/min.md
@@ -24,16 +24,16 @@ specific language governing permissions and limitations
 under the License.
 -->
 
-# MIN
-## Description
-### Syntax
+## MIN
+### Description
+#### Syntax
 
 `MIN(expr)`
 
 
 Returns the minimum value of an expr expression
 
-## example
+### example
 ```
 MySQL > select min(scan_rows) from log_statis group by datetime;
 +------------------+
@@ -42,5 +42,5 @@ MySQL > select min(scan_rows) from log_statis group by datetime;
 |                0 |
 +------------------+
 ```
-## keyword
+### keywords
 MIN
diff --git a/docs/en/sql-manual/sql-functions/aggregate-functions/min_by.md b/docs/en/sql-manual/sql-functions/aggregate-functions/min_by.md
@@ -24,16 +24,16 @@ specific language governing permissions and limitations
 under the License.
 -->
 
-# MIN_BY
-## description
-### Syntax
+## MIN_BY
+### description
+#### Syntax
 
 `MIN_BY(expr1, expr2)`
 
 
 Returns the value of an expr1 associated with the minimum value of expr2 in a group.
 
-## example
+### example
 ```
 MySQL > select * from tbl;
 +------+------+------+------+
@@ -52,5 +52,5 @@ MySQL > select min_by(k1, k4) from tbl;
 |                  4 |
 +--------------------+ 
 ```
-## keyword
+### keywords
 MIN_BY