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Data Engineering →mediumMultiple ChoiceObjective-mapped

MLS-C01 Data Engineering Practice Question

This MLS-C01 practice question tests your understanding of data engineering. This is a configuration task: choose the command set that satisfies every stated requirement. Small differences — like 'secret' vs 'password' or 'transport input ssh' vs 'all' — change whether the answer is correct. 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 engineering team is building a pipeline to process terabytes of log data daily using Amazon EMR with Spark. The data arrives in hourly batches and must be processed within 4 hours. The team needs to minimize cost. Which cluster configuration is MOST cost-effective?

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.

A
Use a single large instance with multiple cores to avoid data shuffling.
Why wrong: Single instance limits parallelism and increases runtime.
B
Use a transient cluster with a mix of on-demand and spot instances, terminated after the job completes.
Transient clusters reduce idle cost, spot instances lower compute cost.
C
Use a long-running cluster of on-demand instances to avoid startup time.
Why wrong: Long-running clusters incur cost even when idle.
D
Use Amazon EMR Serverless to automatically scale.
Why wrong: EMR Serverless may be less cost-effective for large, predictable workloads.

Full breakdown with real-world context →

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 transient cluster with a mix of on-demand and spot instances, terminated after the job completes.

Option B is correct because a transient cluster with a mix of on-demand and spot instances minimizes cost for batch workloads that have a defined lifecycle. Spot instances offer significant discounts (up to 90%) for fault-tolerant Spark jobs, and terminating the cluster after processing eliminates idle compute charges. This approach aligns with the 4-hour processing window and hourly batch arrival, as EMR can provision and tear down clusters quickly.

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 a single large instance with multiple cores to avoid data shuffling.
Why it's wrong here
Single instance limits parallelism and increases runtime.
✓
Use a transient cluster with a mix of on-demand and spot instances, terminated after the job completes.
Why this is correct
Transient clusters reduce idle cost, spot instances lower compute cost.
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 long-running cluster of on-demand instances to avoid startup time.
Why it's wrong here
Long-running clusters incur cost even when idle.
✗
Use Amazon EMR Serverless to automatically scale.
Why it's wrong here
EMR Serverless may be less cost-effective for large, predictable workloads.

Common exam traps

Common exam trap: answer the scenario, not the keyword

The trap here is that candidates overestimate the cost savings of EMR Serverless or long-running clusters, failing to recognize that transient spot-based clusters are the most cost-effective for fixed-window batch processing due to zero idle time and spot pricing discounts.

Detailed technical explanation

How to think about this question

Under the hood, EMR uses YARN or Kubernetes to manage Spark executors; spot instances can be reclaimed with a 2-minute termination notice, but Spark's speculative execution and checkpointing can recover lost tasks. The transient cluster pattern leverages EMR's ability to bootstrap with custom bootstrap actions and install dependencies in under 10 minutes, making it ideal for hourly batch jobs. In practice, using a mix of 70% spot and 30% on-demand instances (for core nodes) balances cost savings with reliability, as seen in production pipelines processing 10+ TB daily.

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 MLS-C01 question test?

Data Engineering — This question tests Data Engineering — Read the scenario before looking for a memorised answer..

What is the correct answer to this question?

The correct answer is: Use a transient cluster with a mix of on-demand and spot instances, terminated after the job completes. — Option B is correct because a transient cluster with a mix of on-demand and spot instances minimizes cost for batch workloads that have a defined lifecycle. Spot instances offer significant discounts (up to 90%) for fault-tolerant Spark jobs, and terminating the cluster after processing eliminates idle compute charges. This approach aligns with the 4-hour processing window and hourly batch arrival, as EMR can provision and tear down clusters quickly.

What should I do if I get this MLS-C01 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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This MLS-C01 practice question is part of Courseiva's free Amazon Web Services 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 MLS-C01 exam.