The answer is to create the table using LOCATION 's3://my-bucket/logs/2023/' which includes all files under that prefix. This works because an Athena table definition points to an S3 prefix as a logical container, automatically including every object within that path regardless of size; the CLI command shown only filtered objects larger than 1000 bytes for display, but it did not alter the underlying data or the table’s scope. On the AWS Certified Machine Learning Specialty MLS-C01 exam, this tests your understanding that Athena’s LOCATION clause performs no server-side filtering—it simply reads the entire prefix at query time, so any size-based restriction must be applied in the table’s schema or via a WHERE clause after scanning. A common trap is confusing a CLI filter with a permanent table constraint; remember that Athena tables are metadata pointers, not data copies. Memory tip: “LOCATION is a door, not a sieve—it lets everything in the prefix through.”
MLS-C01 Exploratory Data Analysis Practice Question
This MLS-C01 practice question tests your understanding of exploratory data analysis. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. 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.
Network Topology
Refer to the exhibit. A data scientist runs the AWS CLI command shown and gets the output. The scientist wants to create an Athena table over all log files in the 'logs/2023/' prefix, including files smaller than 1000 bytes. Which approach achieves this?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Create the table using LOCATION 's3://my-bucket/logs/2023/' which includes all files under that prefix.
The CLI command filters objects larger than 1000 bytes, but the scientist wants all files in the prefix. The Athena table definition should point to the entire prefix without size filtering. Option A is wrong because the command was run locally, not affecting Athena. Option B is wrong because adding a WHERE clause in Athena only filters after scanning. Option D is wrong because the scientist can still create the table without size restrictions.
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.
✓
Create the table using LOCATION 's3://my-bucket/logs/2023/' which includes all files under that prefix.
Why this is correct
The table location covers all files regardless of size.
Related concept
Read the scenario before looking for a memorised answer.
✗
Create the table and add a WHERE clause to include small files.
Why it's wrong here
WHERE clause filters rows after scan, does not include missing files.
✗
Ask the S3 team to remove the size restriction on the bucket.
Why it's wrong here
There is no bucket-level size restriction.
✗
Modify the CLI command to remove the size filter and re-run it before creating the table.
Why it's wrong here
The CLI command is independent of Athena table creation.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Trap categories for this question
Command / output trap
The CLI command is independent of Athena table creation.
Detailed technical explanation
How to think about this question
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
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.
Use explanations to understand the rule behind the answer.
TExam Day Tips
→Underline the problem statement mentally.
→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 MLS-C01 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
Exploratory Data Analysis — This question tests Exploratory Data Analysis — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Create the table using LOCATION 's3://my-bucket/logs/2023/' which includes all files under that prefix. — The CLI command filters objects larger than 1000 bytes, but the scientist wants all files in the prefix. The Athena table definition should point to the entire prefix without size filtering. Option A is wrong because the command was run locally, not affecting Athena. Option B is wrong because adding a WHERE clause in Athena only filters after scanning. Option D is wrong because the scientist can still create the table without size restrictions.
What should I do if I get this MLS-C01 question wrong?
Identify which MLS-C01 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
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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