cloud: Polish availability and limitation of Vector Search (#19494) (#…

…19519)
pingcap · Nov 28, 2024 · e692a15 · e692a15
1 parent c48c3b4
commit e692a15
Show file tree

Hide file tree

Showing 16 changed files with 242 additions and 217 deletions.
diff --git a/package-lock.json b/package-lock.json
diff --git a/package.json b/package.json
@@ -17,5 +17,8 @@
     "micromark-extension-mdxjs": "^1.0.0",
     "octokit": "^3.1.0",
     "unist-util-visit": "^4.1.0"
+  },
+  "devDependencies": {
+    "prettier": "3.3.3"
   }
 }
diff --git a/tidb-cloud/vector-search-data-types.md b/tidb-cloud/vector-search-data-types.md
@@ -18,9 +18,9 @@ Using vector data types provides the following advantages over using the [`JSON`
 - Dimension enforcement: You can specify a dimension to forbid inserting vectors with different dimensions.
 - Optimized storage format: Vector data types are optimized for handling vector data, offering better space efficiency and performance compared to `JSON` types.
 
-> **Note:**
+> **Note**
 >
-> Vector data types are only available for [TiDB Cloud Serverless](/tidb-cloud/select-cluster-tier.md#tidb-cloud-serverless) clusters.
+> TiDB Vector Search is only available for TiDB Self-Managed (TiDB >= v8.4) and [TiDB Cloud Serverless](/tidb-cloud/select-cluster-tier.md#tidb-cloud-serverless). It is not available for [TiDB Cloud Dedicated](/tidb-cloud/select-cluster-tier.md#tidb-cloud-dedicated).
 
 ## Syntax
 
@@ -231,9 +231,9 @@ Currently, direct casting between Vector and other data types (such as `JSON`) i
 
 Note that vector data type columns stored in a table cannot be converted to other data types using `ALTER TABLE ... MODIFY COLUMN ...`.
 
-## Restrictions
+## Limitations
 
-For restrictions on vector data types, see [Vector search limitations](/tidb-cloud/vector-search-limitations.md) and [Vector index restrictions](/tidb-cloud/vector-search-index.md#restrictions).
+See [Vector data type limitations](/tidb-cloud/vector-search-limitations.md#vector-data-type-limitations).
 
 ## MySQL compatibility
 
@@ -243,4 +243,4 @@ Vector data types are TiDB specific, and are not supported in MySQL.
 
 - [Vector Functions and Operators](/tidb-cloud/vector-search-functions-and-operators.md)
 - [Vector Search Index](/tidb-cloud/vector-search-index.md)
-- [Improve Vector Search Performance](/tidb-cloud/vector-search-improve-performance.md)
+- [Improve Vector Search Performance](/tidb-cloud/vector-search-improve-performance.md)
diff --git a/tidb-cloud/vector-search-functions-and-operators.md b/tidb-cloud/vector-search-functions-and-operators.md
@@ -9,25 +9,25 @@ This document lists the functions and operators available for Vector data types.
 
 > **Note**
 >
-> Vector data types and these vector functions are only available for [TiDB Cloud Serverless](/tidb-cloud/select-cluster-tier.md#tidb-cloud-serverless) clusters.
+> TiDB Vector Search is only available for TiDB Self-Managed (TiDB >= v8.4) and [TiDB Cloud Serverless](/tidb-cloud/select-cluster-tier.md#tidb-cloud-serverless). It is not available for [TiDB Cloud Dedicated](/tidb-cloud/select-cluster-tier.md#tidb-cloud-dedicated).
 
 ## Vector functions
 
 The following functions are designed specifically for [Vector data types](/tidb-cloud/vector-search-data-types.md).
 
 **Vector distance functions:**
 
-| Function Name                                             | Description                                                      |
-| --------------------------------------------------------- | ---------------------------------------------------------------- |
+| Function Name                                               | Description                                                      |
+| ----------------------------------------------------------- | ---------------------------------------------------------------- |
 | [`VEC_L2_DISTANCE`](#vec_l2_distance)                       | Calculates L2 distance (Euclidean distance) between two vectors  |
 | [`VEC_COSINE_DISTANCE`](#vec_cosine_distance)               | Calculates the cosine distance between two vectors               |
 | [`VEC_NEGATIVE_INNER_PRODUCT`](#vec_negative_inner_product) | Calculates the negative of the inner product between two vectors |
 | [`VEC_L1_DISTANCE`](#vec_l1_distance)                       | Calculates L1 distance (Manhattan distance) between two vectors  |
 
 **Other vector functions:**
 
-| Function Name                   | Description                                         |
-| ------------------------------- | --------------------------------------------------- |
+| Function Name                     | Description                                         |
+| --------------------------------- | --------------------------------------------------- |
 | [`VEC_DIMS`](#vec_dims)           | Returns the dimension of a vector                   |
 | [`VEC_L2_NORM`](#vec_l2_norm)     | Calculates the L2 norm (Euclidean norm) of a vector |
 | [`VEC_FROM_TEXT`](#vec_from_text) | Converts a string into a vector                     |
@@ -48,17 +48,17 @@ For more information about how vector arithmetic works, see [Vector Data Type |
 
 **Aggregate (GROUP BY) functions:**
 
-| Name                              | Description                                      |
-| :----------------------- | :----------------------------------------------- |
+| Name                                                                                                          | Description                                      |
+| :------------------------------------------------------------------------------------------------------------ | :----------------------------------------------- |
 | [`COUNT()`](https://dev.mysql.com/doc/refman/8.0/en/aggregate-functions.html#function_count)                  | Return a count of the number of rows returned    |
 | [`COUNT(DISTINCT)`](https://dev.mysql.com/doc/refman/8.0/en/aggregate-functions.html#function_count-distinct) | Return the count of a number of different values |
 | [`MAX()`](https://dev.mysql.com/doc/refman/8.0/en/aggregate-functions.html#function_max)                      | Return the maximum value                         |
 | [`MIN()`](https://dev.mysql.com/doc/refman/8.0/en/aggregate-functions.html#function_min)                      | Return the minimum value                         |
 
 **Comparison functions and operators:**
 
-| Name                                  | Description                                           |
-| ---------------------------------------- | ----------------------------------------------------- |
+| Name                                                                                                                | Description                                           |
+| ------------------------------------------------------------------------------------------------------------------- | ----------------------------------------------------- |
 | [`BETWEEN ... AND ...`](https://dev.mysql.com/doc/refman/8.0/en/comparison-operators.html#operator_between)         | Check whether a value is within a range of values     |
 | [`COALESCE()`](https://dev.mysql.com/doc/refman/8.0/en/comparison-operators.html#function_coalesce)                 | Return the first non-NULL argument                    |
 | [`=`](https://dev.mysql.com/doc/refman/8.0/en/comparison-operators.html#operator_equal)                             | Equal operator                                        |
@@ -67,8 +67,8 @@ For more information about how vector arithmetic works, see [Vector Data Type |
 | [`>=`](https://dev.mysql.com/doc/refman/8.0/en/comparison-operators.html#operator_greater-than-or-equal)            | Greater than or equal operator                        |
 | [`GREATEST()`](https://dev.mysql.com/doc/refman/8.0/en/comparison-operators.html#function_greatest)                 | Return the largest argument                           |
 | [`IN()`](https://dev.mysql.com/doc/refman/8.0/en/comparison-operators.html#operator_in)                             | Check whether a value is within a set of values       |
-| [`IS NULL`](https://dev.mysql.com/doc/refman/8.0/en/comparison-operators.html#operator_is-null)                     | Test whether a value is `NULL`                                     |
-| [`ISNULL()`](https://dev.mysql.com/doc/refman/8.0/en/comparison-operators.html#function_isnull)                     | Test whether the argument is `NULL`                     |
+| [`IS NULL`](https://dev.mysql.com/doc/refman/8.0/en/comparison-operators.html#operator_is-null)                     | Test whether a value is `NULL`                        |
+| [`ISNULL()`](https://dev.mysql.com/doc/refman/8.0/en/comparison-operators.html#function_isnull)                     | Test whether the argument is `NULL`                   |
 | [`LEAST()`](https://dev.mysql.com/doc/refman/8.0/en/comparison-operators.html#function_least)                       | Return the smallest argument                          |
 | [`<`](https://dev.mysql.com/doc/refman/8.0/en/comparison-operators.html#operator_less-than)                         | Less than operator                                    |
 | [`<=`](https://dev.mysql.com/doc/refman/8.0/en/comparison-operators.html#operator_less-than-or-equal)               | Less than or equal operator                           |
@@ -80,19 +80,19 @@ For more information about how vectors are compared, see [Vector Data Type | Com
 
 **Control flow functions:**
 
-| Name                                                                                              | Description                  |
-| :------------------------------------------------------------------------------------------------ | :--------------------------- |
-| [`CASE`](https://dev.mysql.com/doc/refman/8.0/en/flow-control-functions.html#operator_case)       | Case operator                |
-| [`IF()`](https://dev.mysql.com/doc/refman/8.0/en/flow-control-functions.html#function_if)         | If/else construct            |
-| [`IFNULL()`](https://dev.mysql.com/doc/refman/8.0/en/flow-control-functions.html#function_ifnull) | Null if/else construct       |
+| Name                                                                                              | Description                    |
+| :------------------------------------------------------------------------------------------------ | :----------------------------- |
+| [`CASE`](https://dev.mysql.com/doc/refman/8.0/en/flow-control-functions.html#operator_case)       | Case operator                  |
+| [`IF()`](https://dev.mysql.com/doc/refman/8.0/en/flow-control-functions.html#function_if)         | If/else construct              |
+| [`IFNULL()`](https://dev.mysql.com/doc/refman/8.0/en/flow-control-functions.html#function_ifnull) | Null if/else construct         |
 | [`NULLIF()`](https://dev.mysql.com/doc/refman/8.0/en/flow-control-functions.html#function_nullif) | Return `NULL` if expr1 = expr2 |
 
 **Cast functions:**
 
-| Name                                                                                        | Description                    |
-| :------------------------------------------------------------------------------------------ | :----------------------------- |
+| Name                                                                                        | Description                        |
+| :------------------------------------------------------------------------------------------ | :--------------------------------- |
 | [`CAST()`](https://dev.mysql.com/doc/refman/8.0/en/cast-functions.html#function_cast)       | Cast a value as a string or vector |
-| [`CONVERT()`](https://dev.mysql.com/doc/refman/8.0/en/cast-functions.html#function_convert) | Cast a value as a string |
+| [`CONVERT()`](https://dev.mysql.com/doc/refman/8.0/en/cast-functions.html#function_convert) | Cast a value as a string           |
 
 For more information about how to use `CAST()`, see [Vector Data Type | Cast](/tidb-cloud/vector-search-data-types.md#cast).
 
@@ -222,7 +222,7 @@ Examples:
 VEC_L2_NORM(vector)
 ```
 
-Calculates the [L2 norm](https://en.wikipedia.org/wiki/Norm_(mathematics)) (Euclidean norm) of a vector using the following formula:
+Calculates the [L2 norm](<https://en.wikipedia.org/wiki/Norm_(mathematics)>) (Euclidean norm) of a vector using the following formula:
 
 $NORM(p)=\sqrt {\sum \limits _{i=1}^{n}{p_{i}^{2}}}$
 

diff --git a/tidb-cloud/vector-search-get-started-using-python.md b/tidb-cloud/vector-search-get-started-using-python.md
@@ -11,7 +11,7 @@ Throughout this tutorial, you will develop this AI application using [TiDB Vecto
 
 > **Note**
 >
-> TiDB Vector Search is currently in beta and is not available for [TiDB Cloud Dedicated](/tidb-cloud/select-cluster-tier.md#tidb-cloud-dedicated) clusters.
+> TiDB Vector Search is only available for TiDB Self-Managed (TiDB >= v8.4) and [TiDB Cloud Serverless](/tidb-cloud/select-cluster-tier.md#tidb-cloud-serverless). It is not available for [TiDB Cloud Dedicated](/tidb-cloud/select-cluster-tier.md#tidb-cloud-dedicated).
 
 ## Prerequisites
 
@@ -54,28 +54,28 @@ pip install sqlalchemy pymysql sentence-transformers tidb-vector python-dotenv
 
 3. Ensure the configurations in the connection dialog match your operating environment.
 
-    - **Connection Type** is set to `Public`.
-    - **Branch** is set to `main`.
-    - **Connect With** is set to `SQLAlchemy`.
-    - **Operating System** matches your environment.
+   - **Connection Type** is set to `Public`.
+   - **Branch** is set to `main`.
+   - **Connect With** is set to `SQLAlchemy`.
+   - **Operating System** matches your environment.
 
-    > **Tip:**
-    >
-    > If your program is running in Windows Subsystem for Linux (WSL), switch to the corresponding Linux distribution.
+   > **Tip:**
+   >
+   > If your program is running in Windows Subsystem for Linux (WSL), switch to the corresponding Linux distribution.
 
 4. Click the **PyMySQL** tab and copy the connection string.
 
-    > **Tip:**
-    >
-    > If you have not set a password yet, click **Generate Password** to generate a random password.
+   > **Tip:**
+   >
+   > If you have not set a password yet, click **Generate Password** to generate a random password.
 
 5. In the root directory of your Python project, create a `.env` file and paste the connection string into it.
 
-    The following is an example for macOS:
+   The following is an example for macOS:
 
-    ```dotenv
-    TIDB_DATABASE_URL="mysql+pymysql://<prefix>.root:<password>@gateway01.<region>.prod.aws.tidbcloud.com:4000/test?ssl_ca=/etc/ssl/cert.pem&ssl_verify_cert=true&ssl_verify_identity=true"
-    ```
+   ```dotenv
+   TIDB_DATABASE_URL="mysql+pymysql://<prefix>.root:<password>@gateway01.<region>.prod.aws.tidbcloud.com:4000/test?ssl_ca=/etc/ssl/cert.pem&ssl_verify_cert=true&ssl_verify_identity=true"
+   ```
 
 ### Step 4. Initialize the embedding model
 
@@ -192,4 +192,4 @@ Therefore, according to the output, the swimming animal is most likely a fish, o
 ## See also
 
 - [Vector Data Types](/tidb-cloud/vector-search-data-types.md)
-- [Vector Search Index](/tidb-cloud/vector-search-index.md)
+- [Vector Search Index](/tidb-cloud/vector-search-index.md)
diff --git a/tidb-cloud/vector-search-get-started-using-sql.md b/tidb-cloud/vector-search-get-started-using-sql.md
@@ -16,7 +16,7 @@ This tutorial demonstrates how to get started with TiDB Vector Search just using
 
 > **Note**
 >
-> TiDB Vector Search is currently in beta and is not available for [TiDB Cloud Dedicated](/tidb-cloud/select-cluster-tier.md#tidb-cloud-dedicated) clusters.
+> TiDB Vector Search is only available for TiDB Self-Managed (TiDB >= v8.4) and [TiDB Cloud Serverless](/tidb-cloud/select-cluster-tier.md#tidb-cloud-serverless). It is not available for [TiDB Cloud Dedicated](/tidb-cloud/select-cluster-tier.md#tidb-cloud-dedicated).
 
 ## Prerequisites
 
@@ -39,9 +39,9 @@ To complete this tutorial, you need:
 
 5. Copy the connection command and paste it into your terminal. The following is an example for macOS:
 
-    ```bash
-    mysql -u '<prefix>.root' -h '<host>' -P 4000 -D 'test' --ssl-mode=VERIFY_IDENTITY --ssl-ca=/etc/ssl/cert.pem -p'<password>'
-    ```
+   ```bash
+   mysql -u '<prefix>.root' -h '<host>' -P 4000 -D 'test' --ssl-mode=VERIFY_IDENTITY --ssl-ca=/etc/ssl/cert.pem -p'<password>'
+   ```
 
 ### Step 2. Create a vector table