Question 1,464 of 1,755
Data EngineeringhardMultiple ChoiceObjective-mapped

Quick Answer

The answer is to configure the SageMaker training job to use Pipe mode, which streams data directly from S3 without downloading to the instance’s local storage. This is the most cost-effective and efficient solution because Pipe mode eliminates the lengthy data download step required by File mode, instead feeding the training algorithm a continuous stream of data from S3 as the job runs. For a 10 TB Parquet dataset, this drastically reduces startup time and overall training time by avoiding local disk bottlenecks and the need for larger instances. On the AWS Certified Machine Learning Specialty MLS-C01 exam, this question tests your understanding of SageMaker input modes and their impact on training performance; a common trap is choosing File mode with larger instances or adding data acceleration services, which incur unnecessary cost. Remember the key distinction: File mode downloads first, Pipe mode streams live. A helpful memory tip is “Pipe it, don’t pile it”—Pipe mode pipes data in as needed, while File mode piles it all onto the disk first.

MLS-C01 Data Engineering Practice Question

This MLS-C01 practice question tests your understanding of data engineering. 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 uses Amazon SageMaker to train and deploy machine learning models. The training data is stored in Amazon S3 (Parquet format, 10 TB). The data scientists have been running training jobs using the File mode input, but the jobs are taking too long due to data download time. They want to reduce the training start-up time and overall training time. Which solution is MOST cost-effective and efficient?

Question 1hardmultiple choice
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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

Configure the SageMaker training job to use Pipe mode, which streams data directly from S3 without downloading to the instance's local storage.

Pipe mode in SageMaker streams training data directly from Amazon S3 to the training algorithm without first downloading it to the instance's local storage. This eliminates the data download step, significantly reducing startup time and overall training time for large datasets like 10 TB. It is the most cost-effective because it avoids the need for larger instances or additional data transfer acceleration services.

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 the SageMaker training job to use Pipe mode, which streams data directly from S3 without downloading to the instance's local storage.

    Why this is correct

    Pipe mode reduces start-up time by streaming data, and it is cost-effective as it avoids EBS volume costs associated with File mode.

    Related concept

    Read the scenario before looking for a memorised answer.

  • Use S3 Transfer Acceleration to speed up the data transfer from S3 to the training instance.

    Why it's wrong here

    S3 Transfer Acceleration optimizes uploads over long distances, but training jobs download data; it does not apply to SageMaker training jobs.

  • Use larger EC2 instances with more vCPUs and memory to speed up the training process.

    Why it's wrong here

    Larger instances may speed up computation but do not reduce the data download time; they increase cost unnecessarily.

  • Enable Elastic Fabric Adapter (EFA) on the training instances to improve network throughput.

    Why it's wrong here

    EFA is designed for inter-node communication, not for S3 data loading; it does not address the download bottleneck.

Common exam traps

Common exam trap: answer the scenario, not the keyword

The trap here is that candidates often confuse Pipe mode with File mode, assuming both require downloading data, or they over-engineer the solution by choosing expensive network accelerators or larger instances when the simplest streaming approach is both faster and cheaper.

Detailed technical explanation

How to think about this question

Pipe mode uses a Linux FIFO (named pipe) to stream data directly from S3 into the training algorithm, allowing the algorithm to start processing as soon as the first bytes arrive. This is especially beneficial for algorithms that can process data sequentially, such as linear learners or tree-based models, but may not be suitable for algorithms that require random access to the dataset. Under the hood, SageMaker uses the S3 API to read objects in chunks and writes them to the pipe, enabling near-zero startup latency for large datasets.

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.

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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: Configure the SageMaker training job to use Pipe mode, which streams data directly from S3 without downloading to the instance's local storage. — Pipe mode in SageMaker streams training data directly from Amazon S3 to the training algorithm without first downloading it to the instance's local storage. This eliminates the data download step, significantly reducing startup time and overall training time for large datasets like 10 TB. It is the most cost-effective because it avoids the need for larger instances or additional data transfer acceleration services.

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.

What is the key concept behind this question?

Read the scenario before looking for a memorised answer.

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Last reviewed: Jun 11, 2026

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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.