- A
Read the CSV in a DoFn and perform a BigQuery query each time an event is processed
Why wrong: Querying BigQuery per event is expensive, slow, and not scalable. It also incurs unnecessary costs.
- B
Use a side input that reads the CSV once and broadcasts it to all workers
Side inputs are designed for such use cases. The CSV is read as a bounded PCollection and used as a side input (e.g., as a Map), enabling efficient, low-latency joins without external calls.
- C
Implement a custom sink that writes events to Cloud SQL and performs a SQL JOIN there
Why wrong: This introduces an external database dependency, adds latency, and increases operational complexity. Not the simplest or most cost-effective.
- D
Use CoGroupByKey to join the stream and batch PCollections by a common key after reading the CSV into a batch PCollection each window
Why wrong: CoGroupByKey works for two bounded PCollections or one unbounded with global window; this approach would require windowing on the batch side and is not the simplest or most cost-effective for a small table.
PDE Designing Data Processing Systems Practice Question
This PDE practice question tests your understanding of designing data processing systems. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A data pipeline ingests streaming events into Pub/Sub and needs to join them with a slowly updating reference table (few thousand rows) from a Cloud Storage CSV file. The pipeline runs on Dataflow with Apache Beam. Which approach is most cost-effective and operationally simple?
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 side input that reads the CSV once and broadcasts it to all workers
Side inputs allow you to read the reference data once and distribute it to all workers, avoiding repeated lookups to an external service. For a small reference table, this is efficient and simple. Option A is complex and overkill; Option B adds latency; Option D is not a native Beam feature.
Key principle: Count usable hosts — not total addresses — and remember that the network and broadcast addresses are not available to hosts in standard IPv4 subnets.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Read the CSV in a DoFn and perform a BigQuery query each time an event is processed
Why it's wrong here
Querying BigQuery per event is expensive, slow, and not scalable. It also incurs unnecessary costs.
- ✓
Use a side input that reads the CSV once and broadcasts it to all workers
Why this is correct
Side inputs are designed for such use cases. The CSV is read as a bounded PCollection and used as a side input (e.g., as a Map), enabling efficient, low-latency joins without external calls.
Related concept
CIDR notation defines the prefix length.
- ✗
Implement a custom sink that writes events to Cloud SQL and performs a SQL JOIN there
Why it's wrong here
This introduces an external database dependency, adds latency, and increases operational complexity. Not the simplest or most cost-effective.
- ✗
Use CoGroupByKey to join the stream and batch PCollections by a common key after reading the CSV into a batch PCollection each window
Why it's wrong here
CoGroupByKey works for two bounded PCollections or one unbounded with global window; this approach would require windowing on the batch side and is not the simplest or most cost-effective for a small table.
Common exam traps
Common exam trap: usable hosts are not the same as total addresses
Subnetting questions often tempt you into counting all addresses. In normal IPv4 subnets, the network and broadcast addresses are not usable host addresses.
Detailed technical explanation
How to think about this question
Subnetting questions test whether you can identify the network, broadcast address, usable range, mask and correct subnet. Slow down enough to calculate the block size correctly.
KKey Concepts to Remember
- CIDR notation defines the prefix length.
- Block size helps identify subnet boundaries.
- Network and broadcast addresses are not usable hosts in normal IPv4 subnets.
- The required host count determines the smallest suitable subnet.
TExam Day Tips
- Write the block size before choosing the subnet.
- Check whether the question asks for hosts, subnets or a specific address range.
- Do not confuse /24, /25, /26 and /27 host counts.
Key takeaway
Count usable hosts — not total addresses — and remember that the network and broadcast addresses are not available to hosts in standard IPv4 subnets.
Real-world example
How this comes up in practice
A startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.
What to study next
Got this wrong? Here's your next step.
Review block sizes, usable host formulas (2^n − 2), and how to find network and broadcast addresses for /24 through /30. Then practise related PDE subnetting questions on CIDR, address ranges, and subnet selection.
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FAQ
Questions learners often ask
What does this PDE question test?
Designing Data Processing Systems — This question tests Designing Data Processing Systems — CIDR notation defines the prefix length..
What is the correct answer to this question?
The correct answer is: Use a side input that reads the CSV once and broadcasts it to all workers — Side inputs allow you to read the reference data once and distribute it to all workers, avoiding repeated lookups to an external service. For a small reference table, this is efficient and simple. Option A is complex and overkill; Option B adds latency; Option D is not a native Beam feature.
What should I do if I get this PDE question wrong?
Review block sizes, usable host formulas (2^n − 2), and how to find network and broadcast addresses for /24 through /30. Then practise related PDE subnetting questions on CIDR, address ranges, and subnet selection.
What is the key concept behind this question?
CIDR notation defines the prefix length.
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Last reviewed: Jul 4, 2026
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.
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