This MLS-C01 practice question tests your understanding of modeling. 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 machine learning engineer is training a deep learning model using the SageMaker built-in XGBoost algorithm. The training job is taking longer than expected. The engineer notices that the training data is stored in S3 in CSV format and is 500 GB in size. The instance type is ml.c4.8xlarge with 10 instances. Which change would most likely reduce training time?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue: "most likely"
Why it matters: Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Use Pipe input mode instead of File input mode.
Pipe input mode streams data directly from S3 to the training instances without first downloading it to the local EBS volume, eliminating the I/O bottleneck of reading a 500 GB CSV file. This reduces the time spent on data loading and allows the XGBoost algorithm to begin training sooner, which is especially beneficial for large datasets.
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.
✗
Convert the data to Parquet format.
Why it's wrong here
Parquet may help but XGBoost built-in algorithm does not support Parquet directly.
✗
Increase the number of instances to 20.
Why it's wrong here
Increasing instances may not help if the bottleneck is data loading.
✓
Use Pipe input mode instead of File input mode.
Why this is correct
Pipe mode streams data directly, reducing I/O bottleneck.
Clue confirmation
The clue word "most likely" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
✗
Increase the size of the EBS volume attached to each instance.
Why it's wrong here
EBS volume size does not affect data loading speed.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Cisco often tests the distinction between data format optimization (Parquet) and data ingestion mode (Pipe vs. File), where candidates mistakenly choose a format change without recognizing that the primary bottleneck is the data transfer mechanism, not the storage format.
Detailed technical explanation
How to think about this question
Pipe input mode uses the SageMaker 'Pipe' channel, which streams data via a Unix pipe (FIFO) directly into the algorithm's input stream, bypassing the local filesystem entirely. This is particularly effective for algorithms like XGBoost that can consume data incrementally, as it overlaps data loading with training, reducing the time-to-first-epoch. In contrast, File mode first downloads the entire 500 GB dataset to each instance's EBS volume, which can take significant time even with high-bandwidth S3 connections.
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 media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
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.
Modeling — This question tests Modeling — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Use Pipe input mode instead of File input mode. — Pipe input mode streams data directly from S3 to the training instances without first downloading it to the local EBS volume, eliminating the I/O bottleneck of reading a 500 GB CSV file. This reduces the time spent on data loading and allows the XGBoost algorithm to begin training sooner, which is especially beneficial for large datasets.
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: "most likely". Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Question Discussion
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