Question 105 of 500
Advanced Searching and StatisticsmediumMultiple SelectObjective-mapped

Quick Answer

The correct answer is that the stats command can produce multiple output columns by using multiple stats functions, and it supports a BY clause to group results by one or more fields. This is technically accurate because the BY clause acts like a SQL GROUP BY, partitioning your events into groups based on distinct field values, then applying aggregate functions such as count, sum, or avg to each group separately. On the Splunk Core Certified Power User SPLK-1003 exam, this concept tests your ability to summarize and transform event data efficiently, often appearing in scenario-based questions where you must choose the right combination of functions and grouping fields. A common trap is confusing the BY clause with the OVER clause used in other commands, or forgetting that multiple stats functions in a single command create separate output columns for each function. To remember, think of “stats with BY” as “group and crunch”—the BY clause defines the groups, and the functions define the crunching.

SPLK-1003 Advanced Searching and Statistics Practice Question

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 statements about the 'stats' command are true?

Question 1mediummulti select
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Answer choices

Why each option matters

Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.

Correct answer & explanation

It can be used with a BY clause to group results.

Option A is correct because the 'stats' command in Splunk supports a BY clause that allows you to group results by one or more fields, similar to a SQL GROUP BY. This enables you to compute aggregate statistics (e.g., count, sum, avg) for each distinct value of the specified field(s), which is a core feature for summarizing event data.

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.

  • It can be used with a BY clause to group results.

    Why this is correct

    The BY clause allows grouping by one or more fields.

    Related concept

    Read the scenario before looking for a memorised answer.

  • The count() function must always include a field argument.

    Why it's wrong here

    count() can be used without a field to count events.

  • It creates one event per input event by default.

    Why it's wrong here

    stats aggregates events, reducing them to one row per group (or overall).

  • It can be used to modify individual field values in raw events.

    Why it's wrong here

    stats does not modify raw events; it produces statistical summaries.

  • It can produce multiple output columns by using multiple stats functions.

    Why this is correct

    Multiple functions can be used in a single stats command, e.g., stats count, avg(bytes).

    Related concept

    Read the scenario before looking for a memorised answer.

Common exam traps

Common exam trap: answer the scenario, not the keyword

Splunk often tests the misconception that 'stats' works like 'eval' or 'rex' to modify raw events, or that count() always requires a field, when in fact count() without a field is a valid and common usage.

Detailed technical explanation

How to think about this question

Under the hood, the 'stats' command uses an in-memory aggregation engine that processes events in streaming fashion, but it must see all events in a time window (or search result set) to compute final aggregates. A subtle behavior is that when using multiple stats functions in one command (e.g., stats count, avg(duration) by host), Splunk automatically creates separate output columns for each function, which is why Option E is correct. In real-world scenarios, this is critical for building dashboards that show both counts and averages per host without needing multiple searches.

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-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

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.

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FAQ

Questions learners often ask

What does this SPLK-1003 question test?

Advanced Searching and Statistics — This question tests Advanced Searching and Statistics — Read the scenario before looking for a memorised answer..

What is the correct answer to this question?

The correct answer is: It can be used with a BY clause to group results. — Option A is correct because the 'stats' command in Splunk supports a BY clause that allows you to group results by one or more fields, similar to a SQL GROUP BY. This enables you to compute aggregate statistics (e.g., count, sum, avg) for each distinct value of the specified field(s), which is a core feature for summarizing event data.

What should I do if I get this SPLK-1003 question wrong?

Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.

What is the key concept behind this question?

Read the scenario before looking for a memorised answer.

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Last reviewed: Jun 30, 2026

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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.