Realtime Compute for Apache Flink:Use the Visual Studio Code extension

Prerequisites

• A workspace is created. For more information, see Activate Realtime Compute for Apache Flink.

• An AccessKey ID and an AccessKey secret are obtained and the permissions related to the namespace you want to use are granted. For more information, see How do I view information about the AccessKey ID and AccessKey secret of the account? and Authorize an account to perform operations in a namespace.

• Visual Studio Code 1.74.0 or later is installed. For more information, visit the Visual Studio Code website.

Limits

• The extension does not support log configuration.

• The extension cannot synchronize deployments created in the development console of Realtime Compute for Apache Flink.

Install and configure the extension

1. Download and install the extension.

   • Method 1: Go to the Visual Studio Code Marketplace page and click Install.

   • Method 2:

     1. Open Visual Studio Code on your computer. In the left-side navigation pane, click EXTENSIONS.

     2. Enter Flink Realtime Compute Studio in the search box.

     3. Find the matched extension and click Install.

2. In the top navigation bar, choose File > Open Folder and select the folder you want to use.

3. Configure the AccessKey pair.

   Configure only for the current folder

   1. In the left-side navigation pane, click . In the Configure AK&SK section, click Configure in a .vvprc file. The extension automatically creates a file suffixed with .vvprc.

      

   2. Open the created file and add the following configurations:

      {
        "accessKey": "xxx",
        "secretKey": "xxx",
        "namespace": "xxx",
        "workspace": "xxx",
        "regionId" : "xxx"
      }

      Parameter	Description	References
      accessKey	The AccessKey ID of your Alibaba Cloud account.	How do I view information about the AccessKey ID and AccessKey secret of the account?
      secretKey	The AccessKey secret of your Alibaba Cloud account.
      namespace	The name of the Realtime Compute for Apache Flink namespace you want to use.	View and delete a namespace
      workspace	The ID of the Realtime Compute for Apache Flink workspace you want to use.	How do I view information about a workspace, such as the workspace ID?
      regionId	The ID of the region in which the workspace is created.	Endpoints

   Configure for the current workspace or user

   1. In the left-side navigation pane, click .

   2. In the Configure AK&SK section, click Configure in global user settings to open the Settings editor in Visual Studio Code.

      

   3. Select the User or Workspace tab based on your business requirements.

      Note

      We recommend that you select the User tab. This way, the parameter configurations apply to all projects and workspaces in Visual Studio Code.

      Parameter	Description	References
      Access Key	The AccessKey ID of your Alibaba Cloud account.	How do I view information about the AccessKey ID and AccessKey secret of the account?
      Secret Key	The AccessKey secret of your Alibaba Cloud account.	How do I view information about the AccessKey ID and AccessKey secret of the account?
      Namespace	The name of the Realtime Compute for Apache Flink namespace you want to use.	View and delete a namespace
      Workspace	The ID of the Realtime Compute for Apache Flink workspace you want to use.	How do I view information about a workspace, such as the workspace ID?
      Region ID	The ID of the region in which the workspace is created.	Endpoints

   Note

   Configuration precedence: Current-folder configuration > Workspace configuration > User configuration.

   After the configurations take effect, the name of the Realtime Compute for Apache Flink namespace is displayed in the status bar in the lower part of the code editor.

4. (Optional) Install the following extensions to improve coding efficiency:

   • Flink SQL Language Features: supports the syntax of Apache Flink SQL.

   • YAML VS Code: provides inline code completions for configurations related to Realtime Compute for Apache Flink.

Use the extension

Step 1: Create a deployment

• Method 1: In the left-side navigation pane, click . In the QUICK START section, click Create a new deployment. In the top navigation bar, enter a name and press the Enter key to create a file suffixed with .vvp. The file includes pre-populated deployment configurations.

  

• Method 2: Create a file suffixed with .vvp in the current folder. The file includes pre-populated deployment configurations.

Step 2: Configure the deployment

You can configure the deployment in the form view.

If you are familiar with the parameters, you can also click Raw File in the upper left corner to configure the deployment in the raw file view. You can click the name of a field in the form to quickly locate the corresponding parameter in the raw file.

• Basic: This section includes basic deployment parameters.

  SQL deployment

  Parameter	Description
  Deployment Name	Enter a name for the deployment.
  Execution Mode	Select the deployment mode. Valid values: STREAM (streaming mode) and BATCH (batch mode).
  Engine Version	Select the version of the Ververica Runtime (VVR) engine. For more information, see Engine versions. We recommend that you select the version labeled with RECOM.
  Deployment Target	Select the queue you want to use for the deployment. For more information, see Manage queues.
  Deployment Type	Select the type of the deployment. In this example, select SQL.
  SQL Script	Click Open in external editor to open the code editor in which you can write DDL and DML statements. Note The changes you make in the code editor are saved in a virtual file. If you exit and reopen Visual Studio Code without closing the editor, the corresponding editor window displays the following error message: The editor could not be opened because the file was not found. To resolve the error, click Open in external editor again.
  Additional Dependencies	Enter the URIs of the additional dependencies required in the deployment.
  Description	Optional. Enter a description for the deployment.

  JAR deployment

  The following table describes the parameters. For more detailed parameter descriptions, see Create a JAR deployment.

  Parameter	Description
  DeploymentName	Enter a name for the deployment.
  Execution Mode	Select the deployment mode. Valid values: STREAM (streaming mode) and BATCH (batch mode).
  Engine Version	Select the version of the VVR engine. For more information, see Engine versions. We recommend that you select the version labeled with RECOM.
  Deployment Target	Select the queue you want to use for the deployment. For more information, see Manage queues.
  Deployment Type	Select the type of the deployment. In this example, select Jar.
  JAR URI	Enter the Object Storage Service (OSS) path or URL of the JAR package you want to use for the deployment. To obtain the OSS path or URL, make sure that you upload the JAR package on the Artifacts page in the development console of Realtime Compute for Apache Flink or in the OSS bucket associated with the workspace.
  Entry Point Class	Enter the entry point class of the Java application. If you do not specify a main class in the JAR package, make sure that you set this parameter to the fully qualified class name of the main class.
  Entry Point Main Arguments	Enter the arguments you want to pass to the main method.
  Additional Dependencies	Enter the OSS path or URL of the additional dependencies required in the deployment. The URL must end with a file name. To obtain the OSS path or URL, make sure that you upload the dependency files on the Artifacts page in the development console of Realtime Compute for Apache Flink or in the OSS bucket associated with the workspace.
  Description	Optional. Enter a description for the deployment.

  Python deployment

  The following table describes the parameters. For more detailed parameter descriptions, see Create a Python deployment.

  Parameter	Description
  Deployment Name	Enter a name for the deployment.
  Execution Mode	Select the deployment mode. Valid values: STREAM (streaming mode) and BATCH (batch mode).
  Engine Version	Select the version of the VVR engine. For more information, see Engine versions. We recommend that you select the version labeled with RECOM.
  Deployment Target	Select the queue you want to use for the deployment. For more information, see Manage queues.
  Deployment Type	Select the type of the deployment. In this example, select Python.
  Python Uri	Enter the URI of the Python deployment file that you want to use. The file can be a .py or .zip file.
  Entry Module	Enter the entry point class of the Python application. If you use a .py file, leave this parameter empty. If you use a. zip file, you must configure this parameter.
  Entry Point Main Arguments	Enter the arguments you want to pass to the main method.
  Python Libraries	Enter the third-party Python libraries you want to use. The specified libraries are automatically passed to the PYTHONPATH environment variable of the corresponding worker process in the deployment. This way, you can use the libraries in Python user-defined functions (UDFs). For information about how to use third-party Python libraries, see Use a third-party Python package.
  Python Archives	Enter the archive files you want to use. For more information, see Use a custom Python virtual environment and Use data files.
  Additional Dependencies	Enter the OSS path or URL of the additional dependencies required in the deployment. To obtain the OSS path or URL, make sure that you upload the dependency files on the Artifacts page in the development console of Realtime Compute for Apache Flink or in the OSS bucket associated with the workspace.
  Description	Optional. Enter a description for the deployment.

• Resources: For information about the parameters in this section, see Configure resources for a deployment.

• Parameters: For information about the parameters in this section, see Parameters section.

Step 3: Submit the deployment

Click Create in the lower part of the editor to submit the deployment. If you update an existing deployment, click Update to submit the updated deployment.

If you submit a SQL deployment, the extension checks the SQL script, resource plan, and other configurations and generates the check result.

Step 4: Start the deployment

After you submit a deployment, the latest status of the deployment is displayed in the upper right corner. Click Start and select a startup mode. For more information about startup modes, see Procedure.

Step 5: Manage the deployment

• To view the detailed running status or perform O&M operations, click Open Online in the upper-left corner to go to the Deployments page in the development console of Realtime Compute for Apache Flink.

• To quickly synchronize a deployment, click Synchronize to open the preview page, confirm the configurations on the preview page, and then click Accept in the upper right corner. This allows the extension to overwrite the configurations by using those from the development console of Realtime Compute for Apache Flink. Take note that the preview page does not display the SQL script updates you perform in the console.

• To cancel a deployment, click Cancel in the upper right corner.

References

• For information about the connectors supported by Realtime Compute for Apache Flink, see Supported connectors.

• For information about how to develop and debug a JAR deployment, see Develop a JAR draft.

• For information about how to develop and debug a Python deployment, see Develop a Python API draft.

• For information about how to improve the performance of SQL deployments, see Optimize Flink SQL.