Google Professional Data Engineer exam dumps

Google Professional Data Engineer practice question 251 of 279

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

Google Professional Data Engineer Question 251

Select 3Google Cloud Platform

You are a Data Engineer managing a streaming data pipeline built with Google Cloud Dataflow. Recently, you noticed an increase in processing latency and suspect a possible bottleneck in the system. Which steps should you take to diagnose and troubleshoot the issue?

  1. A

    Check the Dataflow job's worker CPU and memory utilization metrics in Cloud Monitoring.

  2. B

    Examine the Dataflow job's Input/output throughput metrics to identify potential data skew or backlogs.

  3. C

    Manually restart the Dataflow job to clear any temporary processing issues.

  4. D

    Inspect the logs in Cloud Logging for errors or warnings related to the Dataflow job.

  5. E

    Increase the number of workers in the Dataflow job without further investigation to resolve the latency issue.

Show answer and explanation

Correct answers: A, B, D

Explanation

To troubleshoot a Dataflow job with increased latency, it is essential to identify the root cause by analyzing metrics such as CPU/memory utilization and I/O throughput, and by reviewing logs for errors or warnings. These steps provide valuable insights into potential resource bottlenecks, data skew, or configuration issues. Arbitrary actions like restarting the job or scaling workers without investigation may lead to inefficiencies or data inconsistencies.

  • A. Correct.

    Checking CPU and memory utilization metrics helps identify resource constraints that could be causing the latency.

  • B. Correct.

    Examining I/O throughput metrics can reveal issues like data skew or backlogged data that may be affecting performance.

  • C. Incorrect.

    Manually restarting the job without identifying the root cause is not a reliable troubleshooting step and could lead to data loss or incomplete processing.

  • D. Correct.

    Inspecting logs in Cloud Logging can provide specific error messages or warnings that help diagnose the issue.

  • E. Incorrect.

    Increasing the number of workers without understanding the root cause may temporarily alleviate the issue but could lead to unnecessary costs and might not address the underlying problem.

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