updates

Author: soyeric128

docs/en/sql-reference/10-sql-commands/00-ddl/01-table/92-attach-table.md

@@ -55,89 +55,28 @@ CONNECTION = ( <connection_parameters> )
 
 - `CONNECTION` specifies the connection parameters required for establishing a link to the object storage where the source table's data is stored. The connection parameters vary for different storage services based on their specific requirements and authentication mechanisms. For more information, see [Connection Parameters](../../../00-sql-reference/51-connect-parameters.md).
 
-## Examples
+## Tutorials
 
-This example illustrates how to link a new table in Databend Cloud with an existing table in Databend, which stores data within an Amazon S3 bucket named "databend-toronto".
+- [Linking Tables with ATTACH TABLE](/tutorials/databend-cloud/link-tables)
 
-#### Step 1. Creating Table in Databend
+## Examples
 
-Create a table named "population" and insert some sample data:
+This example creates an attached table, which includes all columns from a source table stored in AWS S3:
 
-```sql title='Databend:'
-CREATE TABLE population (
-  city VARCHAR(50),
-  population INT
+```sql
+ATTACH TABLE population_all_columns 's3://databend-doc/1/16/' CONNECTION = (
+  REGION='us-east-2',
+  AWS_KEY_ID = '<your_aws_key_id>',
+  AWS_SECRET_KEY = '<your_aws_secret_key>'
 );
-
-INSERT INTO population (city, population) VALUES
-  ('Toronto', 2731571),
-  ('Montreal', 1704694),
-  ('Vancouver', 631486);
-```
-
-#### Step 2. Obtaining Database ID and Table ID
-
-Use the [FUSE_SNAPSHOT](../../../20-sql-functions/16-system-functions/fuse_snapshot.md) function to obtain the database ID and table ID. The result below indicates that the database ID is **1**, and the table ID is **556**:
-
-```sql title='Databend:'
-SELECT * FROM FUSE_SNAPSHOT('default', 'population');
-
-┌──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────┐
-│            snapshot_id           │                 snapshot_location                 │ format_version │ previous_snapshot_id │ segment_count │ block_count │ row_count │ bytes_uncompressed │ bytes_compressed │ index_size │          timestamp         │
-├──────────────────────────────────┼───────────────────────────────────────────────────┼────────────────┼──────────────────────┼───────────────┼─────────────┼───────────┼────────────────────┼──────────────────┼────────────┼────────────────────────────┤
-│ f252dd43d1aa44898a04827808342daf │ 1/556/_ss/f252dd43d1aa44898a04827808342daf_v4.mpk │              4 │ NULL                 │             1 │           1 │         3 │                 70 │              448 │        531 │ 2023-11-01 02:35:47.325319 │
-└──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────┘
 ```
 
-When you access the bucket page on Amazon S3, you'll observe that the data is organized within the path `databend-toronto` > `1` > `556`, like this:
-
-![Alt text](/img/sql/attach-table-2.png)
-
-#### Step 3. Linking Table in Databend Cloud
-
-Sign in to Databend Cloud and run the following command in a worksheet to link a table named "population_readonly":
+This example creates an attached table, which includes only selected columns (`city` and `population`) from a source table stored in AWS S3:
 
-```sql title='Databend Cloud:'
-ATTACH TABLE population_readonly 's3://databend-toronto/1/556/' CONNECTION = (
+```sql
+ATTACH TABLE population_only (city, population) 's3://databend-doc/1/16/' CONNECTION = (
+  REGION='us-east-2',
   AWS_KEY_ID = '<your_aws_key_id>',
   AWS_SECRET_KEY = '<your_aws_secret_key>'
 );
-```
-
-To verify the success of the link, run the following query in Databend Cloud:
-
-```sql title='Databend Cloud:'
-SELECT * FROM population_readonly;
-
--- Expected result:
-┌────────────────────────────────────┐
-│       city       │    population   │
-├──────────────────┼─────────────────┤
-│ Toronto          │         2731571 │
-│ Montreal         │         1704694 │
-│ Vancouver        │          631486 │
-└────────────────────────────────────┘
-```
-
-You're all set! If you update the source table in Databend, you can observe the same changes reflected in the target table on Databend Cloud. For example, if you change the population of Toronto to 2,371,571 in the source table:
-
-```sql title='Databend:'
-UPDATE population
-SET population = 2371571
-WHERE city = 'Toronto';
-```
-
-You can see that the updates are synced to the attached table in Databend Cloud:
-
-```sql title='Databend Cloud:'
-SELECT * FROM population_readonly;
-
--- Expected result:
-┌────────────────────────────────────┐
-│       city       │    population   │
-├──────────────────┼─────────────────┤
-│ Toronto          │         2371571 │
-│ Montreal         │         1704694 │
-│ Vancouver        │          631486 │
-└────────────────────────────────────┘
-```
+```

docs/en/tutorials/databend-cloud/link-tables.md

@@ -2,7 +2,7 @@
 title: Linking Tables with ATTACH TABLE
 ---
 
-In this tutorial, we'll walk you through how to link a table in Databend Cloud with an existing Databend table stored in an S3 bucket using the ATTACH TABLE command.
+In this tutorial, we'll walk you through how to link a table in Databend Cloud with an existing Databend table stored in an S3 bucket using the [ATTACH TABLE](/sql/sql-commands/ddl/table/attach-table) command.
 
 ## Before You Start
 
@@ -23,8 +23,8 @@ docker run \
     -e QUERY_STORAGE_TYPE=s3 \
     -e AWS_S3_ENDPOINT="https://s3.us-east-2.amazonaws.com" \
     -e AWS_S3_BUCKET=databend-doc\
-    -e AWS_ACCESS_KEY_ID=<your-aws-access-key-id> \ # Replace with your AWS access key ID
-    -e AWS_SECRET_ACCESS_KEY=<your-aws-secrect-access-key> \ # Replace with your AWS secret access key
+    -e AWS_ACCESS_KEY_ID=<your-aws-access-key-id> \ 
+    -e AWS_SECRET_ACCESS_KEY=<your-aws-secrect-access-key> \ 
     datafuselabs/databend:v1.2.699-nightly
 ```
 
@@ -61,7 +61,7 @@ SELECT snapshot_location FROM FUSE_SNAPSHOT('default', 'population');
 
 2. Execute the following statements to create two attached tables:
     - The first table, `population_all_columns`, includes all columns from the source data.
-    - The second table, `population_withoutprovince`, includes only the selected columns (city & population).
+    - The second table, `population_only`, includes only the selected columns (`city` & `population`).
 
 ```sql
 -- Create an attached table with all columns from the source
@@ -72,7 +72,7 @@ ATTACH TABLE population_all_columns 's3://databend-doc/1/16/' CONNECTION = (
 );
 
 -- Create an attached table with selected columns (city & population) from the source
-ATTACH TABLE population_withoutprovince (city, population) 's3://databend-doc/1/16/' CONNECTION = (
+ATTACH TABLE population_only (city, population) 's3://databend-doc/1/16/' CONNECTION = (
   REGION='us-east-2',
   AWS_KEY_ID = '<your_aws_key_id>',
   AWS_SECRET_KEY = '<your_aws_secret_key>'
@@ -94,7 +94,7 @@ SELECT * FROM population_all_columns;
 │ Vancouver        │ British Columbia │          631486 │
 └───────────────────────────────────────────────────────┘
 
-SELECT * FROM population_withoutprovince;
+SELECT * FROM population_only;
 
 ┌────────────────────────────────────┐
 │       city       │    population   │
@@ -113,4 +113,55 @@ SET population = 2371571
 WHERE city = 'Toronto';
 ```
 
-    After executing the update, you can query the attached table again to see the updated data:
+After executing the update, you can query both attached tables to verify that the changes are reflected:
+
+```sql
+-- Check the updated population in the attached table with all columns  
+SELECT population FROM population_all_columns WHERE city = 'Toronto';
+
+-- Check the updated population in the attached table with only the population column  
+SELECT population FROM population_only WHERE city = 'Toronto';
+```
+
+Expected output for both queries above:
+
+```sql
+┌─────────────────┐
+│    population   │
+├─────────────────┤
+│         2371571 │
+└─────────────────┘
+```
+
+3. If you drop the `province` column from the source table, it will no longer be available in the attached table for queries.
+
+```sql
+ALTER TABLE population DROP province;
+```
+
+After dropping the column, any queries referencing it will result in an error. However, the remaining columns can still be queried successfully.
+
+For example, attempting to query the dropped `province` column will fail:
+
+```sql
+SELECT province FROM population_all_columns;
+error: APIError: QueryFailed: [1065]error:
+  --> SQL:1:8
+  |
+1 | SELECT province FROM population_all_columns
+  |        ^^^^^^^^ column province doesn't exist
+```
+
+However, you can still retrieve the `city` and `population` columns:
+
+```sql
+SELECT city, population FROM population_all_columns;
+
+┌────────────────────────────────────┐
+│       city       │    population   │
+├──────────────────┼─────────────────┤
+│ Toronto          │         2371571 │
+│ Montreal         │         1704694 │
+│ Vancouver        │          631486 │
+└────────────────────────────────────┘
+```