Control-M for Azure Databricks

Azure Databricks is a cloud-based data analytics platform that enables you to process large workloads of data.

Control-M for Azure Databricks enables you to do the following:

  • Connect to any Azure Databricks workspace using service principal authentication.
  • Integrate Azure Databricks jobs with other Control-M jobs into a single scheduling environment.
  • Monitor the Azure Databricks workspace status and view the results in the Monitoring domain.
  • Attach an SLA job to your entire Azure Databricks data service.
  • Introduce all Control-M capabilities to Azure Databricks, including advanced scheduling criteria, complex dependencies, quantitative and control resources, and variables.
  • Run 50 Azure Databricks jobs simultaneously per Control-M/Agent.

Control-M for Azure Databricks Compatibility

The following table lists the prerequisites that are required to use the Azure Databricks plug-in, each with its minimum required version.

ComponentVersion
Control-M/EM9.0.20.200
Control-M/Agent9.0.20.200
Control-M Application Integrator9.0.20.201
Control-M Web9.0.20.200
Control-M Automation API9.0.20.235

Control-M for Azure Databricks is supported on Control-M Web and Control-M Automation API, but not on Control-M client.

To download the required installation files for each prerequisite, see Obtaining Control-M Installation Files.

Setting up Control-M for Azure Databricks

This procedure describes how to deploy the Azure Databricks plug-in, create a connection profile, and define an Azure Databricks job in Control-M Web and Automation API.

NOTE: Integration plug-ins released by BMC require an Application Integrator installation at your site. However, these plug-ins are not editable and you cannot import them into Application Integrator. To deploy these integrations to your Control-M environment, you import them directly into Control-M using Control-M Automation API.

Before you Begin

Verify that Automation API is installed, as described in Automation API Installation.

Begin

  1. Create a temporary directory to save the downloaded files.

  2. Click http://www.bmc.com/available/epd and follow the instructions on the EPD site to download the Azure Databricks plug-in from the Control-M Integrations page, or go directly to the Control-M for Azure Databricks download page.

  3. Deploy the Azure Databricks job via Automation API, as described in deploy jobtype.
  4. Create an Azure Databricks connection profile in Control-M Web or Automation API, as follows:
  5. Define an Azure Databricks job in Control-M Web or Automation API, as follows:
Was this page helpful? Yes No Submitting... Thank you

Comments