Databricks Machine Learning Professional exam dumps

Databricks Machine Learning Professional practice question 122 of 280

Databricks Certified Machine Learning Professional. Professional level, Databricks. Free question with the correct answer and a full explanation.

Databricks Machine Learning Professional Question 122

Select 2

You are managing an MLflow experiment in Databricks and need to clean up unnecessary webhooks as part of your maintenance process. What steps should you take to list all webhooks and delete a specific webhook?

  1. A

    Use the MLflow CLI command mlflow webhooks list to retrieve all webhooks and their IDs, and then use mlflow webhooks delete --id <webhook-id> to delete a specific webhook.

  2. B

    Use the Databricks REST API GET /api/2.0/mlflow/webhooks/list to list all webhooks, and then use DELETE /api/2.0/mlflow/webhooks/delete with the webhook ID to delete a specific webhook.

  3. C

    Use the Databricks UI to navigate to the experiment's Webhooks tab and delete the webhook by clicking the 'Delete' button.

  4. D

    Use the MLflow Python client to call mlflow.webhooks.get_all() to list webhooks and mlflow.webhooks.remove(webhook_id) to delete a webhook.

  5. E

    Write a custom Python script to query the MLflow tracking server's database directly and remove the webhook record.

Show answer and explanation

Correct answers: A, B

Explanation

To manage webhooks in Databricks, you can either use the MLflow CLI or the Databricks REST API. The CLI commands mlflow webhooks list and mlflow webhooks delete allow you to list and delete webhooks, respectively. Alternatively, the REST API endpoints GET /api/2.0/mlflow/webhooks/list and DELETE /api/2.0/mlflow/webhooks/delete provide programmatic access to perform the same actions. Other methods, such as using the Databricks UI or directly modifying the database, are not supported or recommended.

  • A. Correct.

    Correct. The MLflow CLI provides a straightforward way to list and delete webhooks using the list and delete commands.

  • B. Correct.

    Correct. The Databricks REST API allows programmatic access to list and delete webhooks, making it a valid approach for this task.

  • C. Incorrect.

    Incorrect. Currently, the Databricks UI does not provide a dedicated section to manage or delete webhooks directly.

  • D. Incorrect.

    Incorrect. The MLflow Python client does not include direct functions like get_all or remove for webhook management. Webhook operations must use the CLI or REST API.

  • E. Incorrect.

    Incorrect. Modifying the MLflow tracking server's database directly is unsupported and can lead to system instability.

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