Google Professional Data Engineer exam dumps

Google Professional Data Engineer practice question 128 of 279

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

Google Professional Data Engineer Question 128

Select 4Google Cloud Platform

Your company uses Google BigQuery to store and analyze large datasets. Recently, the team has observed performance issues during query execution. You suspect that inefficient data access patterns might be the cause. Which steps should you take to analyze and optimize data access patterns in BigQuery?

  1. A

    Use the BigQuery INFORMATION_SCHEMA.JOBS view to analyze query execution details and identify costly queries.

  2. B

    Examine the query execution plan in the BigQuery Query Plan tab to identify excessive shuffling or large stages.

  3. C

    Enable BigQuery BI Engine to automatically optimize all queries and avoid analyzing query patterns manually.

  4. D

    Check table partitioning and clustering configurations to ensure they align with query patterns.

  5. E

    Review the BigQuery audit logs in Cloud Logging to identify patterns in query frequency and resource usage.

Show answer and explanation

Correct answers: A, B, D, E

Explanation

To analyze and optimize data access patterns in BigQuery, it is essential to use tools and methods that provide insights into query performance and resource usage. This includes examining query execution details, reviewing table configurations like partitioning and clustering, and leveraging audit logs for usage patterns. BigQuery BI Engine can optimize some queries but does not eliminate the need for a thorough analysis of data access patterns.

  • A. Correct.

    The BigQuery INFORMATION_SCHEMA.JOBS view provides detailed information about executed queries, including costs and duration, which can help identify inefficient queries.

  • B. Correct.

    The Query Plan tab in BigQuery helps visualize query execution details, such as data shuffling and stage performance, aiding in identifying bottlenecks.

  • C. Incorrect.

    While BigQuery BI Engine improves query performance for supported dashboards, it does not replace the need for manual analysis of query patterns.

  • D. Correct.

    Partitioning and clustering can significantly impact query performance. Ensuring these configurations align with query patterns is crucial for optimizing data access.

  • E. Correct.

    BigQuery audit logs in Cloud Logging can reveal trends in query usage, helping identify frequent queries and resource-intensive operations.

Timed practice exam

Take a Google Professional Data Engineer practice test under exam conditions

60 questions in 120 minutes, drawn from this bank, with a score report and a per-question review when you finish.

Start timed exam

More Google Professional Data Engineer practice questions

  1. 129.A retail company is designing a scalable system to store customer transaction data. The data...
  2. 130.Your organization is building a high-traffic e-commerce application that requires globally...
  3. 131.Your company is building a real-time recommendation engine for an e-commerce platform. The system...
  4. 132.You are working on a data analytics project that involves processing large volumes of transactional...
  5. 133.Your company is designing a data pipeline for processing large quantities of IoT data. The data...
Back to the Google Professional Data Engineer exam dumps