easyMultiple ChoiceObjective-mapped
PDE Practice Question: A data engineer needs to process large CSV files…
A data engineer needs to process large CSV files (hundreds of GB) stored in Cloud Storage using Spark on a Dataproc cluster. The job performs a series of transformations and aggregations. Which configuration is most cost-effective and operationally efficient?
⚠ Common exam trap
Google Cloud often tests the misconception that preemptible VMs are unreliable for all workloads, but in Spark batch processing with fault tolerance, they are both cost-effective and operationally efficient, unlike stateful or latency-sensitive applications.
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 a cluster with a standard master node and 10 preemptible worker nodes (n1-standard-4).
Preemptible workers are significantly cheaper (about 80% discount) and ideal for batch processing of large CSV files where fault tolerance is built into Spark via RDD lineage. Using standard nodes for the master ensures cluster stability, while preemptible workers handle the distributed transformations and aggregations cost-effectively. This configuration balances cost and operational efficiency for ephemeral, fault-tolerant workloads.
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 a cluster with 10 high-memory (n1-highmem-8) VMs as workers to improve shuffle performance.
Why it's wrong here
High-memory machines are more expensive; standard machines are usually sufficient.
- ✓
Use a cluster with a standard master node and 10 preemptible worker nodes (n1-standard-4).
Why this is correct
Preemptible workers are cost-effective and suitable for fault-tolerant jobs like Spark.
- ✗
Use a single-node cluster with a high-memory machine type.
Why it's wrong here
A single-node cluster cannot efficiently process hundreds of GB due to memory and CPU constraints.
- ✗
Use a cluster with 10 standard (n1-standard-4) VMs as master and worker nodes, all non-preemptible.
Why it's wrong here
Non-preemptible VMs are more expensive; using preemptible workers reduces cost.
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