lake: add incremental updates 427 (#22783)

Author: lilin90

TOC-tidb-cloud-lake.md

@@ -19,7 +19,7 @@ For connections to {{{ .lake }}}, you can use the default `cloudapp` user or an
 
 ### Step 1: Obtain {{{ .lake }}} Connection Information
 
-Log in to {{{ .lake }}} to obtain connection information. For more information, see [Connecting to a Warehouse](/tidb-cloud-lake/guides/warehouse.md#connecting).
+Log in to {{{ .lake }}} to obtain connection information. For more information, see [Connecting to a Warehouse](/tidb-cloud-lake/guides/warehouse.md#connecting-to-a-warehouse).
 
 ![alt text](/media/tidb-cloud-lake/dbeaver-connect-info.png)
 

tidb-cloud-lake/guides/connect-using-dbeaver.md

@@ -27,6 +27,7 @@ summary: "{{{ .lake }}} supports familiar Data Definition Language (DDL) and Dat
 - Grants
 - Warehouse
 - Task
+- [Snapshot Tag](/tidb-cloud-lake/sql/table-versioning.md#snapshot-tags)
 
 ## Organizing Data
 
@@ -35,7 +36,7 @@ Arrange your data in databases and tables.
 Key Commands:
 
 - [`CREATE DATABASE`](/tidb-cloud-lake/sql/create-database.md): To create a new database.
-- [`ALTER DATABASE`](/tidb-cloud-lake/sql/rename-database.md): To modify an existing database.
+- [`ALTER DATABASE`](/tidb-cloud-lake/sql/alter-database.md): To modify an existing database.
 - [`CREATE TABLE`](/tidb-cloud-lake/sql/create-table.md): To create a new table.
 - [`ALTER TABLE`](/tidb-cloud-lake/sql/alter-table.md): To modify an existing table.
 

tidb-cloud-lake/guides/data-lifecycle.md

@@ -15,7 +15,7 @@ This tutorial guides you through the process of integrating {{{ .lake }}} with D
 
 ### Step 1. Set up Environment
 
-Make sure you can log in to your {{{ .lake }}} account and obtain the connection information for a warehouse. For more details, see [Connecting to a Warehouse](/tidb-cloud-lake/guides/warehouse.md#connecting).
+Make sure you can log in to your {{{ .lake }}} account and obtain the connection information for a warehouse. For more details, see [Connecting to a Warehouse](/tidb-cloud-lake/guides/warehouse.md#connecting-to-a-warehouse).
 
 ### Step 2. Connect to {{{ .lake }}}
 

tidb-cloud-lake/guides/deepnote.md

@@ -79,7 +79,7 @@ Every column except the timestamp and line column becomes a LogQL label.
    - **Database**: The database name containing your log table
    - **Warehouse**: The warehouse name
 
-For detailed information on obtaining connection details, see [Connecting to a Warehouse](/tidb-cloud-lake/guides/warehouse.md#connecting).
+For detailed information on obtaining connection details, see [Connecting to a Warehouse](/tidb-cloud-lake/guides/warehouse.md#connecting-to-a-warehouse).
 
 ### Step 3. Configure Grafana Data Source
 
@@ -128,7 +128,7 @@ For advanced use cases requiring direct SQL access or when working with self-hos
 Before you start, ensure you have:
 
 - Grafana installed. Refer to the official installation guide: [https://grafana.com/docs/grafana/latest/setup-grafana/installation](https://grafana.com/docs/grafana/latest/setup-grafana/installation)
-- {{{ .lake }}} access with connection information for a warehouse (see [Connecting to a Warehouse](/tidb-cloud-lake/guides/warehouse.md#connecting))
+- {{{ .lake }}} access with connection information for a warehouse (see [Connecting to a Warehouse](/tidb-cloud-lake/guides/warehouse.md#connecting-to-a-warehouse))
 
 ### Step 2. Modify Grafana Configuration
 

tidb-cloud-lake/guides/grafana.md

@@ -237,7 +237,7 @@ Before you start, ensure that you have [Python](https://www.python.org/) install
 
 ### Step 1. Obtain Connection Information
 
-Obtain the connection information from {{{ .lake }}}. For how to do that, refer to [Connecting to a Warehouse](/tidb-cloud-lake/guides/warehouse.md#connecting).
+Obtain the connection information from {{{ .lake }}}. For how to do that, refer to [Connecting to a Warehouse](/tidb-cloud-lake/guides/warehouse.md#connecting-to-a-warehouse).
 
 ### Step 2. Deploy Jupyter Notebook
 

tidb-cloud-lake/guides/jupyter-notebook.md

@@ -7,7 +7,8 @@ summary: TSV (Tab Separated Values) is a simple file format used to store tabula
 
 ## What is TSV?
 
-TSV (Tab Separated Values) is a simple file format used to store tabular data, such as a spreadsheet or database. The TSV file format is very similar to CSV, the records are separated by newlines, and each field is separated by a tab.
+TSV (Tab Separated Values, called `TEXT` in {{{ .lake }}} `v1.2.890-nightly` and later) is a simple file format used to store tabular data, such as a spreadsheet or database. The TSV file format is very similar to CSV, the records are separated by newlines, and each field is separated by a tab.
+
 The following example shows a TSV file with two records:
 
 ```text
@@ -30,6 +31,10 @@ FROM { userStage | internalStage | externalStage | externalLocation }
 ) ]
 ```
 
+> **Note:**
+>
+> Starting in {{{ .lake }}} `v1.2.890-nightly`, `TEXT` is supported as an alias for `TSV`. This guide keeps `TYPE = TSV` in examples so they continue to work on older server versions. If you only target `v1.2.890-nightly` or later, you can use `TYPE = TEXT` instead.
+
 - For more TSV file format options, refer to [TSV File Format Options](/tidb-cloud-lake/sql/input-output-file-formats.md#tsv-options).
 - For more COPY INTO table options, refer to [COPY INTO table](/tidb-cloud-lake/sql/copy-into-table.md).
 

tidb-cloud-lake/guides/load-tsv.md

@@ -234,5 +234,5 @@ cd agent-ui && npm run dev
 
 - **GitHub Repository**: [databendlabs/mcp-databend](https://github.com/databendlabs/mcp-databend)
 - **PyPI Package**: [mcp-databend](https://pypi.org/project/mcp-databend)
-- **Agno Framework**: [Agno MCP](https://docs.agno.com/tools/mcp/mcp)
+- **Agno Framework**: [Agno MCP](https://docs.agno.com/tools/mcp/overview)
 - **Agent UI**: [Agent UI](https://docs.agno.com/agent-ui/introduction)

tidb-cloud-lake/guides/mcp-server.md

@@ -37,7 +37,7 @@ This tutorial guides you through the process of integrating {{{ .lake }}} / {{{
 
 To follow along, you'll need to install Metabase with Docker. Before you begin, make sure that Docker is installed on your system.
 
-For this tutorial, you will integrate with {{{ .lake }}}. Make sure you can log in to your TiDB Cloud account and obtain the connection information for a warehouse. For more details, see [Connecting to a Warehouse](/tidb-cloud-lake/guides/warehouse.md#connecting).
+For this tutorial, you will integrate with {{{ .lake }}}. Make sure you can log in to your TiDB Cloud account and obtain the connection information for a warehouse. For more details, see [Connecting to a Warehouse](/tidb-cloud-lake/guides/warehouse.md#connecting-to-a-warehouse).
 
 ### Step 2. Deploy Metabase
 

tidb-cloud-lake/guides/metabase.md

@@ -11,7 +11,7 @@ Both {{{ .lake }}} and {{{ .lake }}} can integrate with MindsDB as a data source
 
 ## Tutorial-1: Integrating {{{ .lake }}} with MindsDB
 
-Before you start, install a local MindsDB or sign up an account for MindsDB Cloud. This tutorial uses MindsDB Cloud. For more information about how to install a local MindsDB, refer to <https://docs.mindsdb.com/quickstart#1-create-a-mindsdb-cloud-account-or-install-mindsdb-locally>
+Before you start, install a local MindsDB or sign up an account for MindsDB Cloud. This tutorial uses MindsDB Cloud. For more information about how to install a local MindsDB, refer to <https://docs.mindsdb.com/quickstart-tutorial>.
 
 ### Step 1. Load Dataset into {{{ .lake }}}
 
@@ -100,7 +100,7 @@ WHERE (NO2 = 0.005)
 
 ## Tutorial-2: Integrating {{{ .lake }}} with MindsDB
 
-Before you start, install a local MindsDB or sign up an account for MindsDB Cloud. This tutorial uses MindsDB Cloud. For more information about how to install a local MindsDB, refer to <https://docs.mindsdb.com/quickstart#1-create-a-mindsdb-cloud-account-or-install-mindsdb-locally>
+Before you start, install a local MindsDB or sign up an account for MindsDB Cloud. This tutorial uses MindsDB Cloud. For more information about how to install a local MindsDB, refer to <https://docs.mindsdb.com/quickstart-tutorial>.
 
 ### Step 1. Load Dataset into {{{ .lake }}}
 
@@ -143,7 +143,7 @@ COPY INTO pollution_measurement FROM 'https://repo.databend.com/AirPolutionSeoul
 
     > **Tip:**
     >
-    > The SQL statements above connect the database `default` in {{{ .lake }}} to your MindsDB Cloud account. The parameter values can be obtained from the connection information of your warehouse. For more information, see [Connecting to a Warehouse](/tidb-cloud-lake/guides/warehouse.md#connecting). For explanations about the parameters, refer to <https://docs.mindsdb.com/data-integrations/all-data-integrations#databend>
+    > The SQL statements above connect the database `default` in {{{ .lake }}} to your MindsDB Cloud account. The parameter values can be obtained from the connection information of your warehouse. For more information, see [Connecting to a Warehouse](/tidb-cloud-lake/guides/warehouse.md#connecting-to-a-warehouse). For explanations about the parameters, refer to <https://docs.mindsdb.com/data-integrations/all-data-integrations#databend>
 
 2. In the MindsDB Cloud Editor, run the following SQL statements to verify the integration: