Google Professional Data Engineer exam dumps

Google Professional Data Engineer practice question 253 of 279

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

Google Professional Data Engineer Question 253

Select 3Google Cloud Platform

A data engineering team has implemented a workflow that processes large datasets in BigQuery. Recently, they noticed delays in the execution of the workflow and want to identify the cause. Which tools and techniques should the team use to monitor and troubleshoot the performance of their data processes?

  1. A

    Use Cloud Logging to inspect query execution logs for errors or slow-running queries.

  2. B

    Leverage the BigQuery admin panel to analyze query performance metrics such as slot usage and execution time.

  3. C

    Enable Cloud Monitoring alerts to track BigQuery slot utilization and query failures.

  4. D

    Use Dataproc job logs to analyze BigQuery job performance issues.

  5. E

    Run the BigQuery Query Optimizer tool to automatically rewrite slow queries.

Show answer and explanation

Correct answers: A, B, C

Explanation

To effectively monitor and troubleshoot BigQuery performance issues, teams should use tools like Cloud Logging to examine query details, the BigQuery admin panel for performance metrics, and Cloud Monitoring for proactive alerts on critical BigQuery metrics. These tools complement each other in providing a comprehensive observability solution for data processes. Dataproc job logs and non-existent tools like a 'Query Optimizer' are not applicable for BigQuery-specific workflows.

  • A. Correct.

    Correct: Cloud Logging provides detailed logs that help identify errors or inefficiencies in BigQuery queries, which is crucial for troubleshooting performance issues.

  • B. Correct.

    Correct: The BigQuery admin panel is a primary tool for analyzing query performance metrics like slot usage, execution time, and stages, helping to diagnose inefficiencies.

  • C. Correct.

    Correct: Cloud Monitoring can be configured to send alerts when specific BigQuery metrics like slot utilization or query failures exceed predefined thresholds, aiding in proactive monitoring.

  • D. Incorrect.

    Incorrect: Dataproc job logs are specific to Dataproc workflows and are not applicable for monitoring or troubleshooting BigQuery performance issues.

  • E. Incorrect.

    Incorrect: There is no tool called 'BigQuery Query Optimizer' that rewrites queries automatically. Query optimization must be done manually with guidance from performance metrics and best practices.

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