- A
Use Apache Spark streaming on Dataproc to read from Kafka and write to GCS
Why wrong: Spark streaming is possible but adds complexity; Kafka Connect is simpler for this task.
- B
Use Kafka MirrorMaker to replicate topics to a second cluster that writes to GCS
Why wrong: MirrorMaker is for cluster replication, not direct GCS export.
- C
Use the Pub/Sub connector to publish Kafka messages to Pub/Sub, then a Dataflow job to write to GCS
Why wrong: This adds unnecessary hops and cost with Pub/Sub and Dataflow.
- D
Use Kafka Connect with the GCS Sink Connector to write directly to Cloud Storage
Kafka Connect GCS Sink Connector is purpose-built, simple to configure, and runs on the same Dataproc cluster.
Question 645 of 1,000
PDE Ingesting and Processing the Data Practice Question
This PDE practice question tests your understanding of ingesting and processing the data. 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 company runs Apache Kafka on Dataproc for real-time event streaming. They want to archive the Kafka topics to Cloud Storage for long-term retention and later analysis in BigQuery. Which approach is the 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 Kafka Connect with the GCS Sink Connector to write directly to Cloud Storage
Option D is correct because Kafka Connect with the GCS Sink Connector is purpose-built for exactly this use case: it directly streams Kafka topics to Cloud Storage in Avro, Parquet, or JSON format without requiring intermediate processing clusters or services. This approach minimizes operational overhead (no Spark or Dataflow jobs to manage) and is cost-effective since it runs as a lightweight connector within the existing Kafka ecosystem, leveraging Dataproc's managed Kafka cluster.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Use Apache Spark streaming on Dataproc to read from Kafka and write to GCS
Why it's wrong here
Spark streaming is possible but adds complexity; Kafka Connect is simpler for this task.
- ✗
Use Kafka MirrorMaker to replicate topics to a second cluster that writes to GCS
Why it's wrong here
MirrorMaker is for cluster replication, not direct GCS export.
- ✗
Use the Pub/Sub connector to publish Kafka messages to Pub/Sub, then a Dataflow job to write to GCS
Why it's wrong here
This adds unnecessary hops and cost with Pub/Sub and Dataflow.
- ✓
Use Kafka Connect with the GCS Sink Connector to write directly to Cloud Storage
Why this is correct
Kafka Connect GCS Sink Connector is purpose-built, simple to configure, and runs on the same Dataproc cluster.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
A common mistake in Google exams is to think that streaming data to Cloud Storage requires a full streaming pipeline (Spark, Dataflow) or an intermediary service like Pub/Sub, when in fact Kafka Connect provides a native, lightweight, and cost-effective sink directly to GCS.
Detailed technical explanation
How to think about this question
The Kafka Connect GCS Sink Connector uses the Kafka Connect framework's exactly-once semantics (via offset tracking) to reliably write data to GCS, supporting partitioned output and automatic file rotation based on size or time. Under the hood, it leverages the Hadoop FileSystem API to write to GCS, enabling efficient batch writes that reduce API calls and cost. In real-world scenarios, this connector can handle high-throughput Kafka topics (e.g., 100k+ messages/sec) by scaling the number of connector tasks horizontally within the same Dataproc cluster.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
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.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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FAQ
Questions learners often ask
What does this PDE question test?
Ingesting and Processing the Data — This question tests Ingesting and Processing the Data — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Use Kafka Connect with the GCS Sink Connector to write directly to Cloud Storage — Option D is correct because Kafka Connect with the GCS Sink Connector is purpose-built for exactly this use case: it directly streams Kafka topics to Cloud Storage in Avro, Parquet, or JSON format without requiring intermediate processing clusters or services. This approach minimizes operational overhead (no Spark or Dataflow jobs to manage) and is cost-effective since it runs as a lightweight connector within the existing Kafka ecosystem, leveraging Dataproc's managed Kafka cluster.
What should I do if I get this PDE question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
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Last reviewed: Jul 4, 2026
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