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Maintaining and Automating Data WorkloadsmediumMultiple ChoiceObjective-mapped

PDE Maintaining and Automating Data Workloads Practice Question

You are monitoring a Dataproc cluster and notice that the cluster utilisation is high, but jobs are running slowly. The cluster uses preemptible workers for cost savings. What is the most likely cause of the performance degradation?

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

The preemptible workers are being preempted frequently, causing task retries and slowdowns.

Preemptible workers can be terminated at any time, causing job restarts and slower execution. The high utilisation indicates many workers are preempted, leading to recomputation.

Answer analysis

Option-by-option breakdown

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

  • The primary workers are using standard disks instead of SSDs.

    Why it's wrong here

    Disk type may affect performance but is not the most likely cause given preemptible workers.

  • The preemptible workers are being preempted frequently, causing task retries and slowdowns.

    Why this is correct

    Preemptible workers have a high chance of termination, which affects job performance.

  • The cluster is under-provisioned; increase the number of preemptible workers.

    Why it's wrong here

    Adding more preemptible workers may worsen the issue as they are also preemptible.

  • The cluster is using an older image version; upgrade to the latest.

    Why it's wrong here

    Image version is less likely the root cause.

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