Quick Answer
The answer is `stats count by field_name` and `top field_name`. Both commands generate a table of unique values with counts because `stats count by field_name` groups events by each distinct value of the specified field and outputs a two-column table showing every value alongside its total count, while `top field_name` produces the same structure but automatically sorts the results in descending order by count and limits the output to the most frequent values by default. On the Splunk Core Certified Power User SPLK-1003 exam, this concept tests your understanding of data aggregation and reporting commands, often appearing in questions that ask you to identify which tools can produce frequency tables without manual sorting. A common trap is confusing `top` with `rare` or assuming `stats count` requires a separate sorting command, but both directly fulfill the requirement. Memory tip: think of `stats count by` as the full manual method and `top` as the shortcut that adds automatic ranking—both give you that unique-value-and-count table you need.
This SPLK-1003 practice question tests your understanding of advanced searching and statistics. 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.
Which TWO of the following commands can be used to create a table of unique values for a field, along with their counts?
stats count by field_name
Returns all unique field values with their counts.
fields field_name
Why wrong: Only lists the field name, not values.
rare field_name
Why wrong: Returns only the least common values, not a complete list.
top field_name
Returns the most common field values with counts.
dedup field_name
Why wrong: Removes duplicates but does not provide counts.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
stats count by field_name
The `stats count by field_name` command groups events by the unique values of the specified field and outputs a table with each value and its count. The `top field_name` command also produces a table of the most frequent field values along with their counts, sorted in descending order by count. Both commands generate the required table of unique values with counts.
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.
stats count by field_name
Why this is correct
Returns all unique field values with their counts.
Related concept
Read the scenario before looking for a memorised answer.
fields field_name
Why it's wrong here
Only lists the field name, not values.
rare field_name
Why it's wrong here
Returns only the least common values, not a complete list.
top field_name
Why this is correct
Returns the most common field values with counts.
Related concept
Read the scenario before looking for a memorised answer.
dedup field_name
Why it's wrong here
Removes duplicates but does not provide counts.
Common exam traps
Splunk often tests the distinction between commands that produce counts of all unique values (`stats count by`, `top` with `limit=0`) versus commands that only show a subset (`top` default, `rare`) or do not count at all (`fields`, `dedup`).
Detailed technical explanation
The `stats count by field_name` command uses an internal map-reduce operation to aggregate events by field value, making it efficient for large datasets. The `top` command is essentially a shorthand for `stats count by field_name | sort -count | head N`, but by default it limits output to the top 10 values unless `limit=0` is specified to show all. Understanding the default limits and how to override them is critical for accurate results in production searches.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
A practitioner preparing for the SPLK-1003 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
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Advanced Searching and Statistics — study guide chapter
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Splunk Core Certified Power User SPLK-1003 study guide
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FAQ
Advanced Searching and Statistics — This question tests Advanced Searching and Statistics — Read the scenario before looking for a memorised answer..
The correct answer is: stats count by field_name — The `stats count by field_name` command groups events by the unique values of the specified field and outputs a table with each value and its count. The `top field_name` command also produces a table of the most frequent field values along with their counts, sorted in descending order by count. Both commands generate the required table of unique values with counts.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 30, 2026
This SPLK-1003 practice question is part of Courseiva's free Splunk 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 SPLK-1003 exam.
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