Databricks Data Engineer Professional exam dumps

Databricks Data Engineer Professional practice question 233 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 233

Select 3

You are troubleshooting a slow-performing Spark job on a Databricks cluster and want to analyze the event timeline and performance metrics for the job's stages. Which of the following steps can you take to inspect and diagnose the issue?

  1. A

    Navigate to the Spark UI for the cluster and review the 'Stages' tab for task execution details.

  2. B

    Use the Databricks SQL Analytics Dashboard to visualize the job's execution timeline.

  3. C

    Access the Spark UI through the 'Clusters' tab in Databricks and review the 'Jobs' tab to identify bottlenecks.

  4. D

    Enable Ganglia metrics on the cluster and analyze the time series data.

  5. E

    Download and review the event logs from the Spark UI to inspect detailed execution events.

Show answer and explanation

Correct answers: A, C, E

Explanation

To diagnose performance issues in Spark jobs, you can leverage the Spark UI's 'Stages' and 'Jobs' tabs to analyze task execution and identify bottlenecks. Additionally, downloading and reviewing event logs provides granular details about execution events, which can be critical for troubleshooting. While cluster-wide metrics like Ganglia or unrelated tools like SQL Analytics may provide useful insights for other purposes, they are not specific to Spark job execution analysis.

  • A. Correct.

    Correct: The 'Stages' tab in the Spark UI provides task execution details, including duration, shuffle read/write metrics, and skew information, which are essential for diagnosing performance issues.

  • B. Incorrect.

    Incorrect: The Databricks SQL Analytics Dashboard is not used for inspecting Spark job execution details. It is meant for SQL query performance analysis and visualization.

  • C. Correct.

    Correct: The 'Jobs' tab in the Spark UI helps identify bottlenecks by showing how job stages and tasks are executed, along with their durations and any failures.

  • D. Incorrect.

    Incorrect: Ganglia metrics are not directly used to inspect Spark job execution timelines or stages. They provide cluster-wide performance metrics but lack job-specific insights.

  • E. Correct.

    Correct: Reviewing event logs downloaded from the Spark UI allows for detailed inspection of execution events, including task-level metrics and errors.

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