Databricks Data Engineer Professional exam dumps

Databricks Data Engineer Professional practice question 227 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 227

Select 3

You are tasked with optimizing a Spark application that is running slowly. Upon inspecting the Spark UI, you notice that the 'Tasks' tab shows a high number of task failures, and the 'Jobs' tab displays significant skew in task durations. Which elements of the Spark UI should you investigate further to identify and address the performance issues?

  1. A

    The 'Stages' tab to analyze shuffle read and write metrics for skewed data.

  2. B

    The 'Jobs' tab to view the DAG visualization and identify slow-running jobs.

  3. C

    The 'Executors' tab to check for memory usage and executor failures.

  4. D

    The 'SQL' tab to identify inefficiencies in query execution plans.

  5. E

    The 'Environment' tab to review the configuration settings of the Spark application.

Show answer and explanation

Correct answers: A, C, D

Explanation

To diagnose performance issues in Spark applications, the 'Stages' tab helps identify data skew issues, the 'Executors' tab provides key metrics on memory usage and task failures, and the 'SQL' tab allows you to analyze inefficient query execution plans. These elements of the Spark UI are critical for understanding and addressing root causes of performance bottlenecks.

  • A. Correct.

    The 'Stages' tab provides detailed information on shuffle operations, including data skew. If there is a significant imbalance in shuffle read/write metrics, it could indicate skewed data causing performance degradation.

  • B. Incorrect.

    While the 'Jobs' tab provides an overview of job execution and DAG visualization, it does not provide granular details about task failures or memory issues. It's more suited for high-level monitoring.

  • C. Correct.

    The 'Executors' tab is useful for analyzing executor-specific metrics such as memory usage, storage, and task failures. This can help in identifying executor-related bottlenecks or failures.

  • D. Correct.

    The 'SQL' tab provides insights into the query execution plans, which is crucial for identifying inefficiencies such as full table scans, missing filters, or improper join strategies.

  • E. Incorrect.

    The 'Environment' tab provides a snapshot of the Spark application configuration, but it is not directly tied to identifying task failures or skewed data.

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