Quick Answer
The answer is to use `... | sort date | streamstats sum(sales) as running_total`. This command is correct because `streamstats` calculates a running total cumulative sum by processing events sequentially, adding each event’s sales value to an accumulated total as it moves through the results; however, it requires the data to be in chronological order, which is why the `sort date` command must precede it to ensure the cumulative sum builds correctly day by day. On the Splunk SPLK-1003 exam, this question tests your understanding of streaming statistical commands versus regular stats commands—a common trap is forgetting to sort the data first, which would produce an incorrect running total based on the default event order. Remember the memory tip: “Sort first, then stream—cumulative sums are a sorted dream.”
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.
An analyst wants to create a running total of sales per day over a week. The data has fields: date, sales. Which search would produce a cumulative sum for each day?
... | eval running_total = running_sum(sales)
Why wrong: There is no running_sum eval function in Splunk.
... | sort date | streamstats sum(sales) as running_total
streamstats with sum calculates cumulative sum over sorted events.
... | eventstats sum(sales) as running_total
Why wrong: eventstats adds the total sum to each event, not cumulative.
... | stats sum(sales) by date
Why wrong: This gives daily sums, not a running total.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
... | sort date | streamstats sum(sales) as running_total
Option B is correct because it first sorts the events by date to ensure chronological order, then uses `streamstats` to compute a running (cumulative) sum of sales across each event in that order. `streamstats` processes events sequentially and adds the current value to the accumulated total, producing a cumulative sum per day.
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.
... | eval running_total = running_sum(sales)
Why it's wrong here
There is no running_sum eval function in Splunk.
... | sort date | streamstats sum(sales) as running_total
Why this is correct
streamstats with sum calculates cumulative sum over sorted events.
Related concept
Read the scenario before looking for a memorised answer.
... | eventstats sum(sales) as running_total
Why it's wrong here
eventstats adds the total sum to each event, not cumulative.
... | stats sum(sales) by date
Why it's wrong here
This gives daily sums, not a running total.
Common exam traps
Splunk often tests the distinction between `streamstats` (sequential, cumulative) and `eventstats` (non-sequential, global aggregate), and candidates mistakenly choose `eventstats` thinking it computes a running total because it adds a field to each event.
Detailed technical explanation
Under the hood, `streamstats` maintains a sliding window or accumulator that updates with each event in the specified order; it does not require a `by` clause for a simple running total, but sorting by date is critical to ensure the accumulation reflects chronological progression. In real-world scenarios, this pattern is used for time-series analysis like tracking daily revenue growth or cumulative user sign-ups, where the order of events must be explicitly enforced to avoid incorrect results.
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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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: ... | sort date | streamstats sum(sales) as running_total — Option B is correct because it first sorts the events by date to ensure chronological order, then uses `streamstats` to compute a running (cumulative) sum of sales across each event in that order. `streamstats` processes events sequentially and adds the current value to the accumulated total, producing a cumulative sum per day.
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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