DataWorks:PolarDB for PostgreSQL node

Background information

PolarDB for PostgreSQL is a cloud-native relational database service developed by Alibaba Cloud. It is 100% compatible with PostgreSQL and highly compatible with Oracle syntax. PolarDB for PostgreSQL provides rapid elasticity, high performance, massive storage, high security, and reliability. It also supports Ganos, a multi-dimensional and multi-model spatiotemporal information engine developed by Alibaba Cloud, and the open-source PostGIS geographic information engine. For more information, see PolarDB for PostgreSQL.

Prerequisites

• The business process has been created.

  Data Studio performs engine-specific development operations based on business flows. Before creating a node, create a business flow first. For more information, see Create a business flow.

• A PolarDB for PostgreSQL data source is required.

  Add your PolarDB for PostgreSQL database as a data source in DataWorks. To create a data source, see Manage data sources. For more information about PolarDB for PostgreSQL data sources in DataWorks, see PolarDB data sources.

  Note

  PolarDB for PostgreSQL nodes support only PolarDB for PostgreSQL data sources created with a JDBC connection string.

• A network connection is established between your data source and a resource group.

  You must make sure that the desired data source is connected to the resource group that you want to use. For more information about how to configure network connectivity, see Establish a network connection between a resource group and a data source.

• (Optional; required for Resource Access Management (RAM) users) The RAM user used for task development has been added to the target workspace and assigned either the Development or Workspace Administrator role (which grants broad permissions—assign with caution). For more information about adding members and granting permissions, see Add members to a workspace.

Limits

This feature is supported in the following regions: China (Hangzhou), China (Shanghai), China (Beijing), China (Shenzhen), China (Chengdu), China (Hong Kong), Singapore, Malaysia (Kuala Lumpur), Germany (Frankfurt), US (Silicon Valley), and US (Virginia).

Step 1: Create a PolarDB for PostgreSQL node

1. Log on to the DataWorks console. In the target region, click Data Development and O&M > Data Development in the left-side navigation pane. Select a workspace from the drop-down list and click Go to Data Development.

2. Right-click the target workflow and choose Create Node > Database > PolarDB for PostgreSQL.

3. In the Create Node dialog box, enter a Name for the node and click OK. After the node is created, you can develop and configure the task in the node.

Step 2: Develop the PolarDB for PostgreSQL task

(Optional) Select a PolarDB for PostgreSQL data source

If your workspace has multiple PolarDB for PostgreSQL data sources, select the one you need from the drop-down list on the node editor page. If only one data source exists, it is selected by default.

Develop SQL code: simple example

Write SQL code in the code editor of the PolarDB for PostgreSQL node. Example:

SELECT * FROM usertablename;

Develop SQL code: use scheduling parameters

DataWorks provides Scheduling Parameter to dynamically pass values when tasks run on a schedule. Define variables in your code using the ${variable_name} format, then click Schedule in the right-side pane and go to Scheduling Parameter to assign values. For more information, see Formats of scheduling parameters and Configure and use scheduling parameters.

The following code provides an example.

SELECT '${var}'; -- You can use a scheduling parameter for the var variable.

Step 3: Configure task scheduling

To periodically run the node task, click Scheduling on the right side of the node editing page and configure scheduling settings based on your needs. For more information, see Overview of task scheduling properties.

Step 4: Test task code

Perform the following test operations as needed to verify that the task behaves as expected.

1. (Optional) Select a resource group and assign custom parameter values.

   • Click the icon in the toolbar. In the Parameter dialog box, select the schedule resource group for testing.

   • If your task code uses scheduling parameter variables, assign values to them here for testing. For more information about parameter assignment logic, see Task debugging process.

2. Save and run the task code.

   Click the icon in the toolbar to save your task code. Then click the icon to run the task.

3. (Optional) Perform smoke testing.

   To run smoke testing in the development environment and verify that the scheduled node task executes as expected, perform smoke testing either during or after node submission. For more information, see Perform smoke testing.

Step 5: Submit and publish the task

After configuring the node task, submit and publish it. Once published, the node runs periodically based on its scheduling configuration.

1. Click the icon in the toolbar to save the node.

2. Click the icon in the toolbar to submit the node task.

   In the Submission dialog box, enter a Change Description. Optionally, choose whether to require code review after submission.

   Note

   • You must configure the node’s Rerun attribute and Parent Nodes before you can submit the node.

   • Code review helps ensure code quality and prevents errors caused by unreviewed code being published directly to production. If code review is enabled, the submitted node code must be approved by reviewers before it can be published. For more information, see Code review.

If you are using a workspace in standard mode, after successfully submitting the task, click Publish in the upper-right corner of the node editing page to deploy the task to the production environment. For more information, see Publish a task.

Next steps

Task operations: After a task is committed and published, it runs periodically based on the node's configuration. You can click O&M in the top-right corner of the node editing page to go to the Operation Center and view the scheduling and running status of the scheduled task. For more information, see Managing Scheduled Tasks.