Google Professional Data Engineer exam dumps

Google Professional Data Engineer practice question 247 of 279

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

Google Professional Data Engineer Question 247

Single answerGoogle Cloud Platform

You are a Data Engineer working on a data analytics platform using BigQuery. Your team needs to process a large dataset containing historical sales data for annual reporting. The processing can take a few hours, and there are no immediate deadlines for the results. Which type of query job should you choose, and why?

  1. A

    Interactive query, because it provides immediate results for large datasets.

  2. B

    Batch query, because it is cost-effective for processing large datasets without immediate deadlines.

  3. C

    Interactive query, because it automatically optimizes resource usage for large data processing.

  4. D

    Batch query, because it is required when processing data larger than 1 TB.

Show answer and explanation

Correct answer: B

Explanation

Batch queries in BigQuery are ideal for scenarios where processing does not need to be immediate, offering a cost-effective solution by using BigQuery's batch processing queue. Interactive queries, on the other hand, are suited for scenarios requiring low-latency results but may incur higher costs for long-running jobs. Since the team does not have an immediate deadline, a batch query is the most appropriate choice.

  • A. Incorrect.

    Interactive query is designed for low-latency and real-time use cases, but it is not necessary here since there are no immediate deadlines.

  • B. Correct.

    Batch query is suitable for scenarios where there are no immediate deadlines, and it helps reduce costs by scheduling the job in BigQuery's batch processing queue.

  • C. Incorrect.

    Interactive query does not guarantee optimized resource usage for large datasets and is more expensive for long-running queries compared to batch queries.

  • D. Incorrect.

    Batch query is not strictly required for datasets larger than 1 TB; it is more about the processing needs and deadlines rather than data size.

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