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PDE Practice Question: A data pipeline uses Cloud Composer (Airflow) to…

A data pipeline uses Cloud Composer (Airflow) to orchestrate Dataproc jobs. Each job submits a Spark application that reads from BigQuery and writes to Cloud Storage. The pipeline runs nightly and takes 6 hours. Management wants to reduce costs. Which approach is most effective?

⚠ Common exam trap

Google Cloud often tests the misconception that 'upgrading' storage class or changing billing granularity saves money, when in fact the correct answer involves leveraging cheaper compute resources (preemptible VMs) that are designed for fault-tolerant batch jobs.

Answer choices

Why each option matters

Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.

Correct answer & explanation

Use preemptible VMs for the Dataproc cluster

Preemptible VMs are significantly cheaper (up to 80% discount) than standard VMs and are ideal for fault-tolerant, batch workloads like nightly Dataproc jobs. Since the pipeline runs nightly and takes 6 hours, it can tolerate the occasional preemption of worker nodes by using Spark's built-in resilience (e.g., task retries). This directly reduces compute cost without sacrificing completion, assuming the cluster is configured with enough preemptible workers to handle the workload.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Use preemptible VMs for the Dataproc cluster

    Why this is correct

    Preemptible VMs are cheaper and suitable for batch jobs.

  • Switch to Cloud Dataproc billing per second instead of per minute

    Why it's wrong here

    Dataproc already bills per second; no change possible.

  • Increase the memory of the driver node to improve performance

    Why it's wrong here

    Increasing memory increases cost and may not help if the job is I/O bound.

  • Upgrade the Cloud Storage class from Standard to Nearline

    Why it's wrong here

    Nearline is for archival, not for active writes.

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Written by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

This PDE practice question is part of Courseiva's free Google Cloud certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the PDE exam.