PDE Ingesting and Processing the Data Practice Question
A company wants to stream real-time clickstream data from a website into BigQuery for near-real-time analytics. They expect peaks of 10,000 events per second. Which combination of services is most suitable for ingestion?
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
✓
Pub/Sub → Dataflow → BigQuery (Storage Write API)
Pub/Sub is designed for high-throughput event ingestion, Dataflow provides real-time stream processing, and the BigQuery Storage Write API offers exactly-once semantics and high throughput. Therefore, option C is the most suitable. Option A uses Cloud Functions, which are not designed for high-throughput streaming (10,000 events per second would likely exceed typical limits). Option B sends data directly from the web to Dataflow without a buffer, which could lead to data loss during spikes; Pub/Sub provides a durable buffer. Option D uses legacy streaming inserts, which are deprecated and have lower throughput and no exactly-once guarantees.
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 Storage → Cloud Functions → BigQuery
Why it's wrong here
Cloud Functions are not optimized for high-throughput streaming and would struggle with 10k events/sec.
- ✗
Direct Web → Dataflow → BigQuery
Why it's wrong here
Directly sending data to Dataflow is not a standard pattern; Pub/Sub is needed for buffering and decoupling.
- ✓
Pub/Sub → Dataflow → BigQuery (Storage Write API)
Why this is correct
This is the modern recommended architecture: Pub/Sub for ingestion, Dataflow for processing, Storage Write API for high-throughput streaming ingestion into BigQuery.
- ✗
Pub/Sub → Dataflow → BigQuery (legacy streaming inserts)
Why it's wrong here
Legacy streaming inserts are deprecated and have lower throughput; Storage Write API is recommended.
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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