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PDE Practice Question: Which TWO factors should be considered when…
Which TWO factors should be considered when choosing between Cloud Dataflow and Dataproc for a batch processing pipeline?
⚠ Common exam trap
Google Cloud often tests the misconception that Dataflow only supports Java and that Dataproc requires manual scaling, when in fact both services support multiple languages and Dataproc offers optional autoscaling, but Dataflow's autoscaling is more dynamic and fine-grained.
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
✓
Dataflow is built for data processing patterns, while Dataproc is better for general-purpose compute.
Dataflow is purpose-built for data processing patterns like batch and stream processing with unified programming models (Apache Beam), while Dataproc is optimized for general-purpose compute workloads such as running custom Spark, Hadoop, or ML jobs. Option D is correct because Dataflow provides automatic horizontal autoscaling based on pipeline throughput, whereas Dataproc requires manual cluster sizing or configuration of autoscaling policies, which are not as granular or reactive as Dataflow's.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Dataproc allows custom Docker containers, while Dataflow does not.
Why it's wrong here
Dataflow also supports custom containers.
- ✓
Dataflow is built for data processing patterns, while Dataproc is better for general-purpose compute.
Why this is correct
Dataflow is specialized for data pipelines.
- ✗
Dataproc supports Python, while Dataflow only supports Java.
Why it's wrong here
Dataflow supports Python via Beam.
- ✓
Dataflow provides auto-scaling, while Dataproc requires manual cluster sizing.
Why this is correct
Auto-scaling is a key differentiator for Dataflow.
- ✗
Dataflow supports Java and Python, while Dataproc only supports Java.
Why it's wrong here
Dataproc supports multiple languages including Python, R, Scala.
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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.