Control-M for Google BigQuery

Google BigQuery is a Google Cloud Platform (GCP) computing service that you can use for data storage, processing, and analysis.

Control-M for Google BigQuery enables you to do the following:

• Connect to any Google BigQuery from a single computer with secure login, which eliminates the need to provide authentication.
• Integrate Google BigQuery jobs with other Control-M jobs into a single scheduling environment.
• Monitor the Google BigQuery status and view the results in the Monitoring domain.
• Introduce all Control-M capabilities to Google BigQuery, including advanced scheduling criteria, complex dependencies, quantitative and control resources, and variables.
• Run 50 Google BigQuery jobs simultaneously per Control-M/Agent.

Control-M for Google BigQuery Compatibility

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

Control-M for Google BigQuery 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 Google BigQuery

This procedure describes how to deploy the Google BigQuery plug-in, create a connection profile, and define a Google BigQuery 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 Google BigQuery plug-in from the Control-M Integrations page, or go directly to the Control-M for Google BigQuery download page.

3. Deploy the Google BigQuery job via Automation API, as described in deploy jobtype.
4. Create an Google BigQuery connection profile in Control-M Web or Automation API, as follows:
   • Web: Creating a Centralized Connection Profile with GCP BigQuery Connection Profile Parameters
   • Automation API:  ConnectionProfile:Google BigQuery
5. Define an Google BigQuery job in Control-M Web or Automation API, as follows:
   • Web: Create a Job and then define specific Google BigQuery parameters in Google BigQuery Job parameters.
   • Automation API: Job:Google BigQuery