Question 126 of 499

Quick Answer

The answer is to create an ephemeral Dataproc cluster for each job and delete it after completion, combined with storing data in Cloud Storage rather than HDFS. This approach directly achieves Dataproc ephemeral cluster cost savings by decoupling storage from compute, allowing clusters to spin up only when needed and terminate immediately after job completion. The Cloud Storage connector provides Hadoop-compatible file system access, eliminating the need for persistent HDFS replication and its associated costs. On the Google Professional Data Engineer exam, this scenario tests your understanding of cost optimization patterns for intermittent workloads, often appearing as a trap where candidates mistakenly choose persistent clusters or manual scaling. The key insight is that ephemeral clusters eliminate idle compute costs entirely, while Cloud Storage ensures data persistence without cluster dependency. Memory tip: think "spin up, process, delete" — like a rental car you return immediately after the trip, paying only for the miles driven.

PDE Practice Question: Building and operationalizing data processing systems

This PDE practice question tests your understanding of building and operationalizing 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 company is migrating their on-premises Apache Spark jobs to Google Cloud Dataproc. They want to minimize operational overhead and cost for jobs that run only a few times per day. Which TWO strategies should they adopt? (Choose TWO.)

Clue words in this question

Noticing these words before you look at the options changes how you read each choice.

  • Clue: "minimum / minimize"

    Why it matters: Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.

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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

Store all data in Cloud Storage instead of HDFS, and use the Cloud Storage connector to access it.

Option C is correct because storing data in Cloud Storage decouples storage from compute, allowing ephemeral clusters to be spun up and down without data loss. The Cloud Storage connector provides Hadoop-compatible file system access, eliminating the need for HDFS replication and reducing costs by avoiding persistent cluster storage.

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.

  • Configure HDFS replication factor to 3 to ensure data durability during cluster restarts.

    Why it's wrong here

    D is wrong because Cloud Storage already provides high durability; HDFS replication adds overhead.

  • Rewrite the Spark jobs as Dataflow pipelines to take advantage of serverless processing.

    Why it's wrong here

    E is wrong because rewriting is not necessary and may not be feasible; Dataproc runs Spark natively.

  • Store all data in Cloud Storage instead of HDFS, and use the Cloud Storage connector to access it.

    Why this is correct

    C is correct because Cloud Storage is durable and eliminates HDFS management.

    Clue confirmation

    The clue word "minimum / minimize" in the question point toward this answer.

    Related concept

    Read the scenario before looking for a memorised answer.

  • Create an ephemeral Dataproc cluster for each job and delete it after completion.

    Why this is correct

    A is correct because ephemeral clusters reduce cost and operational overhead for batch jobs.

    Clue confirmation

    The clue word "minimum / minimize" in the question point toward this answer.

    Related concept

    Read the scenario before looking for a memorised answer.

  • Use a small persistent cluster that runs continuously and submit jobs to it.

    Why it's wrong here

    B is wrong because persistent clusters incur cost when idle, countering the goal.

Common exam traps

Common exam trap: answer the scenario, not the keyword

Google Cloud often tests the misconception that persistent clusters are necessary for data durability, but the correct approach for intermittent workloads is to use ephemeral clusters with Cloud Storage to minimize cost and operational overhead.

Detailed technical explanation

How to think about this question

The Cloud Storage connector implements the Hadoop FileSystem API, allowing Spark to read/write data directly to GCS buckets using the gs:// scheme. When using ephemeral clusters, data is persisted in Cloud Storage, so cluster deletion does not affect data durability. The connector uses a configurable replication factor (default 1) at the GCS level, which is managed by Google's infrastructure, not the cluster, reducing overhead.

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?

Building and operationalizing data processing systems — This question tests Building and operationalizing data processing systems — Read the scenario before looking for a memorised answer..

What is the correct answer to this question?

The correct answer is: Store all data in Cloud Storage instead of HDFS, and use the Cloud Storage connector to access it. — Option C is correct because storing data in Cloud Storage decouples storage from compute, allowing ephemeral clusters to be spun up and down without data loss. The Cloud Storage connector provides Hadoop-compatible file system access, eliminating the need for HDFS replication and reducing costs by avoiding persistent cluster storage.

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.

Are there clue words in this question I should notice?

Yes — watch for: "minimum / minimize". Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.

What is the key concept behind this question?

Read the scenario before looking for a memorised answer.

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Last reviewed: Jun 30, 2026

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