Question 41 of 510

Data Models and Best Practices →hardMultiple ChoiceObjective-mapped

SPLK-1002 Data Models and Best Practices Practice Question

This SPLK-1002 practice question tests your understanding of data models and best practices. 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.

You are a Splunk administrator at a financial services company. The company has a distributed Splunk environment with 10 indexers and 2 search heads. You have created a data model named 'transaction_analytics' to analyze financial transactions. The data model is accelerated with a summary range of 7 days. Recently, users have reported that dashboards using this data model are extremely slow, sometimes timing out. You check the acceleration status and see that the summary is 'Building' but never completes. The splunkd.log on the search head shows repeated messages: 'Data model acceleration: query timed out after 300 seconds.' The base search for the data model is: index=transactions sourcetype=fin_events | eval risk_score=if(amount>10000, 'high', 'low') | fields transaction_id, user, amount, risk_score, _time. The data model has one root event with two child datasets: one for high-risk transactions and one for low-risk transactions. The total data volume is about 500 GB per day. The indexer where the summary is built has 16 GB of RAM and the search head has 32 GB. What is the best course of action to resolve the acceleration build timeout?

Clue words in this question

Noticing these words before you look at the options changes how you read each choice.

Clue: "best"
Why it matters: Signals that multiple options may be partially correct. Choose the option that most directly solves the exact problem described, not the one that sounds most complete.
Clue: "never"
Why it matters: Absolute qualifier. True only if the statement has zero exceptions — be cautious of options that seem obvious but break down in edge cases.

Question 1hardmultiple choice

Full question →

A
Modify the base search to remove the eval statement and instead use a lookup or index-time field for risk_score.
Removing the expensive eval reduces search-time computation, allowing the acceleration build to complete within the timeout period.
B
Reduce the summary range to 1 day to limit the amount of data processed.
Why wrong: Reducing summary range reduces data but the underlying slow eval will still cause timeout on the remaining data; not a robust solution.
C
Disable acceleration and rely on real-time searches for the dashboards.
Why wrong: Real-time searches on 500 GB/day will be extremely slow and cause dashboard timeouts.
D
Increase the acceleration.max_time to 600 seconds to allow more time for the build.
Why wrong: Increasing timeout may cause the build to consume more resources and potentially fail again; it does not address the slow base search.

Full breakdown with real-world context →

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

✓

Modify the base search to remove the eval statement and instead use a lookup or index-time field for risk_score.

Option A is correct because the eval statement in the base search forces the acceleration to process every raw event during the summary build, which is computationally expensive and causes the 300-second timeout. By moving the risk_score calculation to index time (e.g., using a calculated field or lookup), the acceleration can use the pre-computed field directly from the indexed data, drastically reducing CPU load and allowing the summary to complete within the timeout window.

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.

✓
Modify the base search to remove the eval statement and instead use a lookup or index-time field for risk_score.
Why this is correct
Removing the expensive eval reduces search-time computation, allowing the acceleration build to complete within the timeout period.
Clue confirmation
The clue words "best", "never" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
✗
Reduce the summary range to 1 day to limit the amount of data processed.
Why it's wrong here
Reducing summary range reduces data but the underlying slow eval will still cause timeout on the remaining data; not a robust solution.
✗
Disable acceleration and rely on real-time searches for the dashboards.
Why it's wrong here
Real-time searches on 500 GB/day will be extremely slow and cause dashboard timeouts.
✗
Increase the acceleration.max_time to 600 seconds to allow more time for the build.
Why it's wrong here
Increasing timeout may cause the build to consume more resources and potentially fail again; it does not address the slow base search.

Common exam traps

Common exam trap: answer the scenario, not the keyword

The trap here is that candidates often focus on increasing timeouts or reducing data volume (options B and D) instead of recognizing that expensive eval operations in the base search are the true bottleneck, and that index-time field extraction is the proper Splunk best practice for acceleration.

Detailed technical explanation

How to think about this question

Under the hood, Splunk data model acceleration uses a scheduled search that runs the base search against the summary range and materializes the results into a tsidx file. The eval statement in the base search prevents the acceleration from using indexed fields directly, forcing a full scan and evaluation of every event. In a real-world scenario with 500 GB/day, this can cause the search head to exceed the default 300-second query timeout (set in limits.conf as [search] max_time), especially if the indexer has limited RAM (16 GB) to handle the intermediate results.

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.

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FAQ

Questions learners often ask

What does this SPLK-1002 question test?

Data Models and Best Practices — This question tests Data Models and Best Practices — Read the scenario before looking for a memorised answer..

What is the correct answer to this question?

The correct answer is: Modify the base search to remove the eval statement and instead use a lookup or index-time field for risk_score. — Option A is correct because the eval statement in the base search forces the acceleration to process every raw event during the summary build, which is computationally expensive and causes the 300-second timeout. By moving the risk_score calculation to index time (e.g., using a calculated field or lookup), the acceleration can use the pre-computed field directly from the indexed data, drastically reducing CPU load and allowing the summary to complete within the timeout window.

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: "best", "never". Signals that multiple options may be partially correct. Choose the option that most directly solves the exact problem described, not the one that sounds most complete.

What is the key concept behind this question?

Read the scenario before looking for a memorised answer.

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Last reviewed: Jun 11, 2026

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