Merge pull request #7180 from taosdata/sangshuduo-fix-typo

fix groupdID typo

documentation20/en/07.advanced-features/docs.md

@@ -17,7 +17,7 @@ The continuous query provided by TDengine differs from the time window calculati
 The following is an example of the smart meter scenario to introduce the specific use of continuous query. Suppose we create a STables and sub-tables through the following SQL statement:
 
 ```sql
-create table meters (ts timestamp, current float, voltage int, phase float) tags (location binary(64), groupdId int);
+create table meters (ts timestamp, current float, voltage int, phase float) tags (location binary(64), groupId int);
 create table D1001 using meters tags ("Beijing.Chaoyang", 2);
 create table D1002 using meters tags ("Beijing.Haidian", 2);
 ...
@@ -357,4 +357,4 @@ This SQL statement will obtain the last recorded voltage value of all smart mete
 
 In scenarios of TDengine, alarm monitoring is a common requirement. Conceptually, it requires the program to filter out data that meet certain conditions from the data of the latest period of time, and calculate a result according to a defined formula based on these data. When the result meets certain conditions and lasts for a certain period of time, it will notify the user in some form.
 
-In order to meet the needs of users for alarm monitoring, TDengine provides this function in the form of an independent module. For its installation and use, please refer to the blog [How to Use TDengine for Alarm Monitoring](https://www.taosdata.com/blog/2020/04/14/1438.html).
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+In order to meet the needs of users for alarm monitoring, TDengine provides this function in the form of an independent module. For its installation and use, please refer to the blog [How to Use TDengine for Alarm Monitoring](https://www.taosdata.com/blog/2020/04/14/1438.html).