Checking Running Processes in Databricks
To check for running processes in Databricks, you can use the Databricks UI to view job runs. Here’s how:
- Access the Databricks UI: Log into your Databricks workspace.
- Navigate to Workflows: Click on Workflows in the sidebar.
- View Job Runs: In the Name column, click on a job name to view its runs.
- Check the Runs Tab: The Runs tab displays a list of currently running and recently completed runs for the selected job.
- Use the Job Runs List: The list view shows details such as start time, run identifier, status, and duration for each run.
Frequently Asked Questions
- Q: How do I stop a running job in Databricks?
- A: To stop a running job, go to the Runs tab, find the active run, and click the kebab menu to select Stop or use the Cancel runs option from the drop-down menu.
- Q: Can I view job runs started by external tools?
- A: Yes, Databricks allows you to view job runs started by external orchestration tools like Apache Airflow or Azure Data Factory.
- Q: How long does Databricks keep job run history?
- A: Databricks maintains a history of job runs for up to 60 days.
- Q: How do I display HTML content in a Databricks notebook?
- A: You can use the displayHTML function in Databricks to display HTML content in a notebook.
- Q: Can I display Markdown output in a Python cell in Databricks?
- A: Currently, displaying Markdown output directly in a Python cell is not natively supported in Databricks. However, you can use a workaround involving the Markdown library.
- Q: How do I configure notifications for job runs in Databricks?
- A: To configure notifications, see the documentation on adding notifications to a job.
- Q: Can I use the Databricks CLI to manage job runs?
- A: Yes, you can use the Databricks CLI to list, get details of, and run jobs by using commands like databricks jobs list, databricks jobs get, and databricks jobs run-now.
Bottom Line
Checking running processes in Databricks is straightforward using the Databricks UI. You can easily view and manage job runs, including those started by external tools. Additionally, Databricks provides tools like the CLI and Jobs API for more advanced management and customization.