Get Started with Data Service

Data Service (beta) enables you to access TiDB Cloud data via an HTTPS request using a custom API endpoint and allows you to seamlessly integrate with any application or service that is compatible with HTTPS.

Tip

TiDB Cloud provides a Chat2Query API for TiDB clusters. After it is enabled, TiDB Cloud will automatically create a system Data App called Chat2Query and a Chat2Data endpoint in Data Service. You can call this endpoint to let AI generate and execute SQL statements by providing instructions.

For more information, see Get started with Chat2Query API.

This document introduces how to quickly get started with TiDB Cloud Data Service (beta) by creating a Data App, developing, testing, deploying, and calling an endpoint. A Data App is a collection of endpoints that you can use to access data for a specific application.

Before you begin

Before creating a Data App, make sure that you have created a TiDB Serverless cluster. If you do not have one, follow the steps in Create a TiDB Serverless cluster to create one.

Get started with a sample Data App

Creating a sample Data App is the best way to get started with Data Service. If your project does not have any Data App yet, you can follow the on-screen instructions on the Data Service page to create a sample Data App and use this App to explore Data Service features.

In the TiDB Cloud console, click Data Service in the left navigation pane.
On the Data Service page, click Create Sample Data App. A dialog is displayed.
In the dialog, update the App name if necessary, select clusters that you want the Data App to access, and then click Create.
The creation process takes a few seconds.
Note
If there is no cluster in your current project, you can click Create New Cluster in the Link Data Sources drop-down list to create one first.
After the sample Data App is automatically created, you can find the App name, a list of endpoints in the left pane, the SQL statements of an endpoint in the middle pane, and instructions about using the sample Data App on the right side.
Follow the instructions on the right side to choose an endpoint and use the curl command to call the endpoint.

Get started with your own Data App

To get started with Data Service, you can also create your own Data App, and then develop, test, deploy, and call endpoints according to the following steps.

Step 1. Create a Data App

To create a Data App, perform the following steps:

In the TiDB Cloud console, click Data Service in the left navigation pane.
On the Data Service page of your project, click Create DataApp in the left pane.
Tip
If this is the first Data App in your project, click Create Data App in the middle of the page.
In the Create Data App dialog, enter a name, a description, and select clusters that you want the Data App to access.
(Optional) To automatically deploy endpoints of the Data App to your preferred GitHub repository and branch, enable Connect to GitHub, and then do the following:
1. Click Install on GitHub, and then follow the on-screen instructions to install TiDB Cloud Data Service as an application on your target repository.
2. Click Authorize to authorize access to the application on GitHub.
3. Specify the target repository, branch, and directory where you want to save the configuration files of your Data App.
Note
- The directory must start with a slash (/). For example, /mydata. If the directory you specified does not exist in the target repository and branch, it will be created automatically.
- The combination of repository, branch, and directory identifies the path of the configuration files, which must be unique among Data Apps. If your specified path is already used by another Data App, you need to specify a new path instead. Otherwise, the endpoints configured in the TiDB Cloud console for the current Data App will overwrite the files in your specified path.
Click Create Data App. The Data Service details page is displayed.
If you have configured to connect your Data App to GitHub, check your specified GitHub directory. You will find that the Data App configuration files have been committed to the directory by tidb-cloud-data-service, which means that your Data App is connected to GitHub successfully.
For your new Data App, Auto Sync & Deployment and Review Draft are enabled by default so you can easily synchronize Data App changes between TiDB Cloud console and GitHub and review changes before the deployment. For more information about the GitHub integration, see Deploy your Data App changes with GitHub automatically.

Step 2. Develop an endpoint

An endpoint is a web API that you can customize to execute SQL statements.

After creating a Data App, a default untitled endpoint is created for you automatically. You can use the default endpoint to access your TiDB Cloud cluster.

If you want to create a new endpoint, locate the newly created Data App and click + Create Endpoint to the right of the App name.

Configure properties

On the right pane, click the Properties tab and set properties for the endpoint, such as:

Path: the path that users use to access the endpoint. The combination of the request method and the path must be unique within a Data App.
Endpoint URL: (read-only) the URL is automatically generated based on the region where the corresponding cluster is located, the service URL of the Data App, and the path of the endpoint. For example, if the path of the endpoint is /my_endpoint/get_id, the endpoint URL is https://<region>.data.tidbcloud.com/api/v1beta/app/<App ID>/endpoint/my_endpoint/get_id.
Request Method: the HTTP method of the endpoint. You can use GET to retrieve data, use POST to create or insert data, use PUT to update or modify data, and use DELETE to delete data.

For more information about endpoint properties, see Configure properties.

Write SQL statements

You can customize SQL statements for the endpoint in the SQL editor, which is the middle pane on the Data Service page.

Select a cluster.
Note
Only clusters that are linked to the Data App are displayed in the drop-down list. To manage the linked clusters, see Manage linked clusters.
On the upper part of the SQL editor, select a cluster on which you want to execute SQL statements from the drop-down list. Then, you can view all databases of this cluster in the Schema tab on the right pane.
Write SQL statements.
Before querying or modifying data, you need to first specify the database in the SQL statements. For example, USE database_name;.
In the SQL editor, you can write statements such as table join queries, complex queries, and aggregate functions. You can also simply type -- followed by your instructions to let AI generate SQL statements automatically.
To define a parameter, you can insert it as a variable placeholder like ${ID} in the SQL statement. For example, SELECT * FROM table_name WHERE id = ${ID}. Then, you can click the Params tab on the right pane to change the parameter definition and test values.
Note
- The parameter name is case-sensitive.
- The parameter cannot be used as a table name or column name.
- In the Definition section, you can specify whether the parameter is required when a client calls the endpoint, the data type, and the default value of the parameter.
- In the Test Values section, you can set the test value for a parameter. The test values are used when you run the SQL statements or test the endpoint. If you do not set the test values, the default values are used.
- For more information, see Configure parameters.
Run SQL statements.
If you have inserted parameters in the SQL statements, make sure that you have set test values or default values for the parameters in the Params tab on the right pane. Otherwise, an error is returned.
To run a SQL statement, select the line of the SQL with your cursor and click Run > Run at cursor.
To run all SQL statements in the SQL editor, click Run. In this case, only the last SQL results are returned.
After running the statements, you can see the query results immediately in the Result tab at the bottom of the page.

Step 3. Test the endpoint (optional)

After configuring an endpoint, you can test the endpoint to verify whether it works as expected before deploying.

To test the endpoint, click Test in the upper-right corner or press F5.

Then, you can see the response in the HTTP Response tab at the bottom of the page. For more information about the response, see Response of an endpoint.

Step 4. Deploy the endpoint

To deploy the endpoint, perform the following steps:

On the endpoint details page, click Deploy in the upper-right corner.
Click Deploy to confirm the deployment. You will get the Endpoint has been deployed prompt if the endpoint is successfully deployed.
On the right pane of the endpoint details page, you can click the Deployments tab to view the deployed history.

Step 5. Call the endpoint

You can call the endpoint by sending an HTTPS request. Before calling an endpoint, you need to first obtain an API key for the Data App.

1. Create an API key

In the left pane of the Data Service page, click the name of your Data App to view its details.
In the Authentication area, click Create API Key.
In the Create API Key dialog box, do the following:
1. (Optional) Enter a description for your API key.
2. Select a role for your API key.
  The role is used to control whether the API key can read or write data to the clusters linked to the Data App. You can select the ReadOnly or ReadAndWrite role:
  - ReadOnly: only allows the API key to read data, such as SELECT, SHOW, USE, DESC, and EXPLAIN statements.
  - ReadAndWrite: allows the API key to read and write data. You can use this API key to execute all SQL statements, such as DML and DDL statements.
3. (Optional) Set a desired rate limit for your API key.
Click Next. The public key and private key are displayed.
Make sure that you have copied and saved the private key in a secure location. After leaving this page, you will not be able to get the full private key again.
Click Done.

For more information about API keys, see API Keys in Data Service.

2. Get the code example

TiDB Cloud generates code examples to help you call an endpoint. To get the code example, perform the following steps:

In the left pane of the Data Service page, click the name of your endpoint, and then click ... > Code Example in the upper-right corner. The Code Example dialog box is displayed.

In the dialog box, select the cluster and database that you want to use to call the endpoint, and then copy the code example.

An example of the curl code example is as follows:

Test Environment
Online Environment

To call a draft version of the endpoint, you need to add the endpoint-type: draft header:

curl --digest --user '<Public Key>:<Private Key>' \
  --request GET 'https://<region>.data.tidbcloud.com/api/v1beta/app/<App ID>/endpoint/<Endpoint Path>' \
  --header 'endpoint-type: draft'

You must deploy your endpoint first before checking the code example in the online environment.

To call the current online version of the endpoint, use the following command:

curl --digest --user '<Public Key>:<Private Key>' \
  --request GET 'https://<region>.data.tidbcloud.com/api/v1beta/app/<App ID>/endpoint/<Endpoint Path>'

Note

By requesting the regional domain <region>.data.tidbcloud.com, you can directly access the endpoint in the region where the TiDB cluster is located.
Alternatively, you can also request the global domain data.tidbcloud.com without specifying a region. In this way, TiDB Cloud will internally redirect the request to the target region, but this might result in additional latency. If you choose this way, make sure to add the --location-trusted option to your curl command when calling an endpoint.

3. Use the code example

Paste the code example in your application and run it. Then, you can get the response of the endpoint.

You need to replace the <Public Key> and <Private Key> placeholders with your API key.
If the endpoint contains parameters, specify the parameter values when calling the endpoint.

After calling an endpoint, you can see the response in JSON format. The following is an example:

{
  "type": "sql_endpoint",
  "data": {
    "columns": [
      {
        "col": "id",
        "data_type": "BIGINT",
        "nullable": false
      },
      {
        "col": "type",
        "data_type": "VARCHAR",
        "nullable": false
      }
    ],
    "rows": [
      {
        "id": "20008295419",
        "type": "CreateEvent"
      }
    ],
    "result": {
      "code": 200,
      "message": "Query OK!",
      "start_ms": 1678965476709,
      "end_ms": 1678965476839,
      "latency": "130ms",
      "row_count": 1,
      "row_affect": 0,
      "limit": 50
    }
  }
}

For more information about the response, see Response of an endpoint.