Quick Answer
The answer is 2, 4, 4. This result comes from understanding how Athena aggregate queries treat NULLs: COUNT(col2) returns only non-null values in that column, which here is 2; COUNT(*) counts every row regardless of NULLs, giving 4; and COUNT(DISTINCT col1) counts unique values across all rows, which are A, B, C, and D, also totaling 4. On the AWS Certified Machine Learning Specialty MLS-C01 exam, this tests your ability to interpret query outputs when preparing or cleaning data for ML pipelines—a common task when using Athena on S3 data lakes. A frequent trap is forgetting that COUNT(column) ignores NULLs while COUNT(*) does not, or miscounting distinct values when duplicates exist. Remember the memory tip: COUNT(*) is the total headcount, COUNT(column) is the headcount of people who showed up, and COUNT(DISTINCT) counts unique names in the room.
This MLS-C01 practice question tests your understanding of exploratory data analysis. 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.
The exhibit shows an Athena query result from a table. What is the output of the query?
3, 3, 4
Why wrong: COUNT(col2) is 2, not 3; COUNT(*) is 4, not 3.
2, 3, 3
Why wrong: COUNT(*) is 4, not 3; distinct col1 is 4, not 3.
2, 4, 4
Correct counts: col2 non-null=2, rows=4, distinct col1=4.
2, 4, 3
Why wrong: COUNT(DISTINCT col1) is 4, not 3.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
2, 4, 4
Option B is correct. COUNT(col2) counts non-null values in col2: rows 1 and 3 have non-null, so 2. COUNT(*) counts all rows: 4. COUNT(DISTINCT col1) counts distinct col1 values: A,B,C,D = 4. Option A is wrong because COUNT(col2) is 2, not 3. Option C is wrong because COUNT(*) is 4, not 3. Option D is wrong because COUNT(DISTINCT col1) is 4, not 3.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
3, 3, 4
Why it's wrong here
COUNT(col2) is 2, not 3; COUNT(*) is 4, not 3.
2, 3, 3
Why it's wrong here
COUNT(*) is 4, not 3; distinct col1 is 4, not 3.
2, 4, 4
Why this is correct
Correct counts: col2 non-null=2, rows=4, distinct col1=4.
Related concept
Read the scenario before looking for a memorised answer.
2, 4, 3
Why it's wrong here
COUNT(DISTINCT col1) is 4, not 3.
Common exam traps
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.
Detailed technical explanation
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.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
A cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
What to study next
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.
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FAQ
Exploratory Data Analysis — This question tests Exploratory Data Analysis — Read the scenario before looking for a memorised answer..
The correct answer is: 2, 4, 4 — Option B is correct. COUNT(col2) counts non-null values in col2: rows 1 and 3 have non-null, so 2. COUNT(*) counts all rows: 4. COUNT(DISTINCT col1) counts distinct col1 values: A,B,C,D = 4. Option A is wrong because COUNT(col2) is 2, not 3. Option C is wrong because COUNT(*) is 4, not 3. Option D is wrong because COUNT(DISTINCT col1) is 4, not 3.
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.
Read the scenario before looking for a memorised answer.
About these practice questions
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Same concept, more angles
These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. The exhibit shows the result of an Athena query. What does the value '5000' represent?
mediumWhy B: Option B is correct because the query counts rows where col1 IS NULL, and the result '5000' is that count. Option A is wrong because the query is not selecting distinct values. Option C is wrong because the query counts NULL rows, not non-NULL. Option D is wrong because total row count was not queried.
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Last reviewed: Jun 20, 2026
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.
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