Databricks Data Engineer Professional exam dumps

Databricks Data Engineer Professional practice question 303 of 313

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

Databricks Data Engineer Professional Question 303

Select 2

You are tasked with deploying a Databricks job from the CLI. The job definition is stored in a JSON file called job_config.json. After the job is deployed, you also need to monitor its status to ensure it runs successfully. Which set of CLI commands should you use to achieve this?

  1. A

    Use the command databricks jobs create --json-file job_config.json to deploy the job and databricks jobs get --job-id <job-id> to monitor the job status.

  2. B

    Use the command databricks jobs submit --json-file job_config.json to deploy the job and databricks jobs get-run --run-id <run-id> to monitor the job status.

  3. C

    Use the command databricks jobs create --json-file job_config.json to deploy the job and databricks jobs list to monitor the job status.

  4. D

    Use the command databricks jobs run-now --job-id <job-id> to deploy the job and databricks jobs runs list to monitor the job status.

  5. E

    Use the command databricks jobs submit --json-file job_config.json to deploy the job and databricks jobs runs get --run-id <run-id> to monitor the job status.

Show answer and explanation

Correct answers: B, E

Explanation

To deploy a Databricks job using the CLI, you can use the databricks jobs submit command with the job definition as a JSON file. For monitoring, the databricks jobs get-run or databricks jobs runs get commands are appropriate as they provide detailed information about a specific run's status using the run ID. Options 2 and 5 correctly cover both deployment and monitoring aspects.

  • A. Incorrect.

    This command is partially correct for deployment (databricks jobs create) but incorrect for monitoring since databricks jobs get does not provide run-specific status.

  • B. Correct.

    This command is correct for deployment (databricks jobs submit) and monitoring (databricks jobs get-run) as it allows submitting the job and checking the status of a specific run using the run ID.

  • C. Incorrect.

    This command is incorrect for monitoring because databricks jobs list only lists all jobs but does not provide status of a specific run.

  • D. Incorrect.

    This command is incorrect for deployment because databricks jobs run-now is used to trigger an existing job, not to deploy a new one. However, databricks jobs runs list can list runs, but it does not provide details about a specific run's status.

  • E. Correct.

    This command is correct for deployment (databricks jobs submit) and monitoring (databricks jobs runs get) as it allows submitting the job and retrieving detailed run-specific information using the run ID.

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