Google Professional Data Engineer exam dumps

Google Professional Data Engineer practice question 267 of 279

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

Google Professional Data Engineer Question 267

Select 3Google Cloud Platform

You are responsible for designing a data processing pipeline on Google Cloud for a retail company. The pipeline processes real-time transactional data using Cloud Dataflow and stores the results in BigQuery. To maintain high availability and reduce the impact of potential failures, which strategies should you implement?

  1. A

    Enable Dataflow autoscaling to dynamically adjust resources based on workload.

  2. B

    Configure BigQuery with table partitions to optimize query performance and reduce downtime during failures.

  3. C

    Implement Dataflow checkpoints to resume processing from the last successful state in case of job failure.

  4. D

    Set up Stackdriver Monitoring and Alerting to track pipeline metrics and notify the team of anomalies.

  5. E

    Run the pipeline exclusively in a single region to minimize latency and ensure data consistency.

Show answer and explanation

Correct answers: A, C, D

Explanation

Maintaining awareness of failures and mitigating their impact in a data pipeline requires implementing strategies like autoscaling, checkpointing, and monitoring. These ensure that the system can handle resource fluctuations, recover from failures, and alert the team to potential issues. While options like table partitioning and single-region setups have their merits, they do not directly address failure mitigation or high availability in the given scenario.

  • A. Correct.

    Enabling Dataflow autoscaling ensures that the pipeline can dynamically adapt to workload changes, reducing the risk of resource exhaustion or over-provisioning during spikes or failures.

  • B. Incorrect.

    While BigQuery table partitions optimize query performance, they do not directly address availability or failure impact mitigation in this scenario.

  • C. Correct.

    Dataflow checkpoints allow the pipeline to resume processing from the last successful state, minimizing the impact of job failures and reducing data reprocessing time.

  • D. Correct.

    Stackdriver Monitoring and Alerting can notify the team of anomalies in real-time, enabling faster response to issues and reducing the impact of failures.

  • E. Incorrect.

    Running the pipeline in a single region increases the risk of regional outages affecting the system. Using multi-region setups is recommended for high availability.

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