The answer is that the stats command omitted the Info severity because it has a count of zero. This happens because stats with count() only generates output for field values that appear in at least one event; after the eval, no events had severity=Info, so its count is zero and it is simply dropped from the results. On the Splunk SPLK-1002 exam, this tests your understanding that stats does not produce zero-count buckets by default—a common trap where candidates expect all severity levels to appear regardless of event count. The key distinction is that stats aggregates existing data, while commands like eventstats or appendpipe can preserve empty buckets. Remember the memory tip: stats counts what it sees, not what it doesn’t.
SPLK-1002 Basic Searching and Transforming Commands Practice Question
This SPLK-1002 practice question tests your understanding of basic searching and transforming commands. Examine the command output carefully: the correct answer depends on what the output actually shows, not on general recall alone. 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.
Exhibit
Refer to the exhibit.
index=main | eval severity = case(error=1, "Error", warning=1, "Warning", 1=1, "Info") | stats count by severity
Refer to the exhibit. A user runs this search. The results show only Error and Warning, but no Info. What is the most likely reason?
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
✓
The stats command omitted the info severity because it has zero count.
The stats command with count() only returns results for field values that have at least one event. Since no events had severity=Info after the eval, Info has a count of zero and is omitted from the output. This is the expected behavior of stats — it does not include zero-count buckets unless explicitly requested with the `usenull=f` or similar options.
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.
✗
The eval command has a syntax error.
Why it's wrong here
The eval syntax is correct.
✓
The stats command omitted the info severity because it has zero count.
Why this is correct
Stats by default only shows values present in data; zero-count categories are omitted.
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.
✗
The sort command filters out Info.
Why it's wrong here
No sort is used.
✗
The case statement does not evaluate to a string for Info.
Why it's wrong here
The condition 1=1 is always true, so it should produce Info.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Splunk often tests the misconception that stats returns all possible values of a field, when in fact it only returns values that appear in the events, omitting zero-count buckets.
Detailed technical explanation
How to think about this question
The stats command aggregates by field values and only returns buckets with non-zero counts by default. This is similar to SQL's GROUP BY without HAVING COUNT > 0 — zero-count groups are suppressed. In Splunk, to include zero-count results, you would need to use `fillnull` or `appendpipe` to add missing combinations, or use `stats count by severity` with `usenull=f` (which still omits zeros). This behavior often surprises users who expect all possible values to appear.
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 practitioner preparing for the SPLK-1002 exam encounters this exact type of scenario on the job. The correct answer here is not the most general option — it is the best answer for the specific constraint described. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Real exam questions reward reading the full scenario before eliminating options, because the constraint defines which answer fits.
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.
Basic Searching and Transforming Commands — This question tests Basic Searching and Transforming Commands — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: The stats command omitted the info severity because it has zero count. — The stats command with count() only returns results for field values that have at least one event. Since no events had severity=Info after the eval, Info has a count of zero and is omitted from the output. This is the expected behavior of stats — it does not include zero-count buckets unless explicitly requested with the `usenull=f` or similar options.
What should I do if I get this SPLK-1002 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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