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PDE Practice Question: A financial company processes transactions in…
A financial company processes transactions in real-time and requires exactly-once processing semantics. They also need to reprocess historical data for backtesting. Which Google Cloud service should they use?
⚠ Common exam trap
Google Cloud often tests the misconception that Cloud Pub/Sub (A) provides exactly-once delivery, but in reality it offers at-least-once delivery, and candidates overlook Dataflow's unified batch/streaming model for reprocessing historical data.
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
✓
Cloud Dataflow
Cloud Dataflow (D) is correct because it provides exactly-once processing semantics via its distributed snapshot mechanism (based on the MillWheel paper) and supports both real-time streaming and batch processing for historical backtesting under a unified programming model. This allows the company to reprocess historical data using the same pipeline code, ensuring consistency across real-time and batch modes.
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 Pub/Sub
Why it's wrong here
Cloud Pub/Sub delivers at-least-once by default and retains messages for a maximum of seven days, so it cannot guarantee exactly-once processing or replay historical data for backtesting. It is tempting because it handles real-time streaming ingestion well, and it would be correct for simple event distribution where duplicate delivery and short retention are acceptable.
- ✗
Cloud Functions
Why it's wrong here
Cloud Functions executes short event-driven snippets without built-in exactly-once stream processing or durable replay of historical data. It fits lightweight triggers and glue logic; the stem's requirement for exactly-once semantics over real-time transactions with backtesting replay is met by Dataflow's windowing and state.
- ✗
Cloud Dataproc
Why it's wrong here
Dataproc runs batch Spark and Hadoop clusters, lacking native exactly-once streaming semantics for real-time transactions. It is the right choice for scheduled batch analytics or migrating existing Spark jobs; here the stem demands continuous exactly-once processing plus replay, which Dataflow provides.
- ✓
Cloud Dataflow
Why this is correct
Cloud Dataflow provides exactly-once processing through its streaming engine and supports replaying bounded historical datasets via the same pipeline code, so backtesting and real-time transaction processing share one model. Pub/Sub alone lacks the reprocessing semantics required here.
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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.