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Ingesting and Processing the DatamediumMultiple ChoiceObjective-mapped

PDE Ingesting and Processing the Data Practice Question

You are migrating an existing Kafka cluster to Google Cloud using Dataproc. The cluster handles high-throughput streaming data with strict ordering requirements per partition. Which choice of Dataproc configuration is most appropriate?

⚠ Common exam trap

Google Cloud often tests the misconception that preemptible VMs or local SSDs are acceptable for stateful, ordered workloads like Kafka, when in fact they violate durability and ordering guarantees due to ephemeral storage and abrupt termination.

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 Dataproc with non-preemptible workers and persistent SSD storage for brokers.

Kafka brokers in a Dataproc cluster require persistent, non-preemptible workers to maintain data durability and strict ordering per partition. Preemptible workers can be terminated at any time, causing data loss or rebalancing that violates ordering guarantees. Persistent SSD storage provides the low-latency I/O needed for high-throughput Kafka workloads, while non-preemptible instances ensure broker stability and consistent replication.

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 Dataflow with Kafka IO instead of Dataproc.

    Why it's wrong here

    The question specifically asks about migrating Kafka to Dataproc, not replacing it with Dataflow.

  • Use Dataproc with local SSDs for better performance, and enable autoscaling.

    Why it's wrong here

    Local SSDs are ephemeral; if the instance terminates, data is lost. Kafka brokers require persistent storage unless replication is very high.

  • Use Dataproc with preemptible workers to reduce cost, and attach standard persistent disks.

    Why it's wrong here

    Preemptible workers are not recommended for stateful streaming workloads like Kafka because they can be terminated at any time, causing data loss or rebalancing.

  • Use Dataproc with non-preemptible workers and persistent SSD storage for brokers.

    Why this is correct

    Non-preemptible workers provide stability for Kafka brokers, and SSDs offer low latency for high-throughput streaming.

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