PDE Ingesting and Processing the Data Practice Question
You need to process a large volume of event data from Cloud Storage, apply complex transformations using Apache Spark, and then load the results into BigQuery. The data arrives in batches every hour. You want to minimize costs by using preemptible VMs. Which service should you use?
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
✓
Dataproc
Dataproc supports preemptible (now called spot) VMs for cost savings. Dataflow does not support preemptible VMs for workers; it uses standard VMs. Cloud Composer is orchestration only. BigQuery is not for running Spark.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Cloud Composer
Why it's wrong here
Cloud Composer is an Airflow orchestrator, not for running Spark jobs directly.
- ✗
BigQuery
Why it's wrong here
BigQuery runs SQL queries, not Spark code.
- ✓
Dataproc
Why this is correct
Dataproc clusters can use preemptible VMs for cost-efficient batch processing with Spark.
- ✗
Dataflow
Why it's wrong here
Dataflow uses managed VMs and does not support preemptible VMs.
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