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.
A user reports that a data model acceleration is consuming excessive disk space on the indexer. The data model has a summary range of 90 days. Which action is best to reduce disk space usage while maintaining acceptable query performance?
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.
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Reduce the summary range to 30 days.
Reducing the summary range from 90 days to 30 days directly decreases the amount of data that the acceleration precomputes and stores on the indexer. This minimizes disk space consumption while still accelerating queries for the most recent, commonly accessed data. Maintaining a shorter summary range ensures acceptable performance for recent queries without the overhead of storing summaries for older, less frequently accessed time periods.
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.
✗
Increase the acceleration frequency to rebuild summaries more often.
Why it's wrong here
More frequent rebuilds may increase disk I/O but not reduce space.
✓
Reduce the summary range to 30 days.
Why this is correct
A shorter summary range reduces the amount of summary data, saving disk space.
Clue confirmation
The clue word "best" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
✗
Disable acceleration for the data model.
Why it's wrong here
Disabling acceleration removes all summaries, impacting query performance.
✗
Delete old indexed data that is not frequently queried.
Why it's wrong here
Deleting indexed data is drastic and may violate retention policies.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates may confuse summary range with acceleration frequency or think that deleting raw data is the primary way to free space, when in fact the acceleration summaries themselves are the direct cause of the disk space issue.
Detailed technical explanation
How to think about this question
Data model acceleration works by creating and storing a set of summary indices (TSIDX files) that contain pre-aggregated results for the specified summary range. These summaries are stored in the `datamodel_summary` bucket type on the indexer, separate from raw data. Reducing the summary range from 90 to 30 days means the acceleration only precomputes and retains summaries for the most recent 30 days, freeing disk space while still allowing fast queries on that window; queries beyond 30 days will fall back to scanning raw data, which is slower but acceptable for occasional historical analysis.
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.
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: Reduce the summary range to 30 days. — Reducing the summary range from 90 days to 30 days directly decreases the amount of data that the acceleration precomputes and stores on the indexer. This minimizes disk space consumption while still accelerating queries for the most recent, commonly accessed data. Maintaining a shorter summary range ensures acceptable performance for recent queries without the overhead of storing summaries for older, less frequently accessed time periods.
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". 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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Question Discussion
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