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PDE Practice Question: Stream data from Cloud Pub/Sub into BigQuery with…
A company wants to stream data from Cloud Pub/Sub into BigQuery with minimal latency. They have a small team and limited operational resources. Which approach is best?
⚠ Common exam trap
Google Cloud often tests the misconception that a simple serverless function (Cloud Function) is sufficient for streaming workloads, but candidates overlook that Cloud Functions are designed for event-driven, short-lived tasks and lack the state management, exactly-once guarantees, and sustained throughput needed for continuous data ingestion into BigQuery.
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 Dataflow pipeline with a BigQuery subscription.
A Dataflow pipeline with a BigQuery subscription provides a fully managed, serverless streaming solution that directly ingests messages from Pub/Sub and writes them to BigQuery with minimal latency. Dataflow handles autoscaling, checkpointing, and exactly-once semantics, which aligns with the team's limited operational resources. The BigQuery subscription (via the Pub/Sub to BigQuery template) eliminates the need for custom code or cluster management, ensuring low-latency streaming without operational overhead.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Write a custom application on Compute Engine that polls Pub/Sub and writes to BigQuery.
Why it's wrong here
Requires management.
- ✗
Create a Dataproc cluster running a Spark Streaming job.
Why it's wrong here
Operational overhead.
- ✗
Create a Cloud Function that writes to BigQuery.
Why it's wrong here
Not suitable for high throughput.
- ✓
Use a Dataflow pipeline with a BigQuery subscription.
Why this is correct
Serverless and low maintenance.
Quick reference
Cloud Service Model Comparison
| Model | You Manage | Provider Manages | Examples |
|---|---|---|---|
| IaaS | OS, runtime, apps, data | Hardware, hypervisor, networking | EC2, Azure VMs, GCP Compute Engine |
| PaaS | Apps and data | OS, runtime, middleware, hardware | Elastic Beanstalk, Azure App Service |
| SaaS | Data and settings only | Everything else | Microsoft 365, Salesforce, Workday |
| FaaS / Serverless | Function code only | Infra, scaling, runtime | Lambda, Azure Functions, Cloud Run |
| CaaS | Containers and apps | Kubernetes, OS, hardware | EKS, AKS, GKE |
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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.