Building a Reusable JDBC Agent for SQL Task Execution

[kissycn]

Hi Argo community,

I am currently researching cloud-native data warehouse orchestration tools, and I plan to use Argo to orchestrate my big data DAG tasks. The common tasks in my workflow include Spark, Flink, Shell, HTTP, and SQL (such as MySQL, SparkSQL, and SQLServer).

The Challenge:

Hi Argo community,
For SQL tasks, typically, each task in my workflow only executes a single SQL query. If I use the standard Argo Workflow steps, each SQL task would spin up a new pod to execute the SQL statement, which can be highly resource-intensive.

To optimize resource usage, I would like to implement a generic, long-running JDBC Agent that can handle all SQL query requests from various workflow tasks. The idea is to maintain only one instance of this JDBC Agent for the entire cluster, avoiding the creation of new pods for each SQL task.

What I Need Help With:

I understand that the Argo community provides options like HTTP Templates and Plugins to create Agents. The HTTP Template interacts with WorkflowTaskSet, but I am still unclear about how Plugins work.

Given my scenario, I would appreciate guidance on the following:

Should I use HTTP Templates or WorkflowTaskSet to build a reusable JDBC Agent?
If I go with HTTP Templates, would I be able to customize it in a similar manner to Plugins?
Looking forward to any insights or recommendations on how to approach this.

Thanks in advance for your help!

[kissycn]

The function I need is similar to this issue. From the current situation, it seems that Global Agent is not supported.

[jswxstw]

If you have already deployed an HTTP server to serve as a reusable JDBC agent, you can use HTTP templates to send SQL execution requests to it, or you can also directly implement a plugin to serve as a reusable JDBC agent.