The correct answer is to increase the memory allocation for the data model acceleration process. This directly resolves the "not enough memory to complete summary build" error, which occurs when the acceleration process exhausts its allocated memory resources during the summary build. In Splunk, data model acceleration pre-computes and stores aggregated data in memory to speed up searches, and when the allocated memory limit is too low for the dataset size, the build fails with this specific error. On the SPLK-1002 exam, this question tests your understanding of resource management in data model acceleration, often appearing as a trap where candidates might mistakenly try to reduce data volume or disable acceleration instead of adjusting memory settings in limits.conf or the acceleration UI. A helpful memory tip: think "RAM for the summary" — when the build runs out of gas, give it more fuel by increasing the memory cap.
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.
During a data model acceleration build, the following error appears in splunkd.log: 'Data model acceleration: not enough memory to complete summary build.' Which best practice should the administrator implement to prevent this error?
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
✓
Increase the memory allocation for the data model acceleration process.
Option B is correct because the error 'not enough memory to complete summary build' indicates that the data model acceleration process has exhausted its allocated memory. Increasing the memory allocation for the data model acceleration process (via the limits.conf or the data model acceleration settings) directly addresses this resource constraint, allowing the summary to build successfully.
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.
✗
Remove unnecessary fields from the data model to reduce complexity.
Why it's wrong here
Removing fields may help but memory error is about process allocation, not field count.
✓
Increase the memory allocation for the data model acceleration process.
Why this is correct
The error indicates insufficient memory; increasing allocation resolves it.
Clue confirmation
The clue word "best" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
✗
Reduce the summary range to less than 7 days.
Why it's wrong here
Reducing range may reduce memory needs but is not a direct fix for memory allocation.
✗
Use tstats instead of data model acceleration for queries.
Why it's wrong here
tstats relies on acceleration; it does not address the build memory error.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse memory errors with data complexity or time range issues, leading them to choose options that reduce data volume (A or C) rather than addressing the specific resource allocation problem (B).
Detailed technical explanation
How to think about this question
Data model acceleration uses a background search to build and store summary statistics in a TSIDX file, which requires memory for sorting and aggregation. The memory allocation is controlled by the 'max_mem_usage_mb' setting in limits.conf under the [datamodelacceleration] stanza; if this limit is too low for the data volume, the build fails. In real-world scenarios, administrators should monitor the 'data_model_acceleration_memory_usage' metric in Splunk Monitoring Console to tune this value appropriately.
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: Increase the memory allocation for the data model acceleration process. — Option B is correct because the error 'not enough memory to complete summary build' indicates that the data model acceleration process has exhausted its allocated memory. Increasing the memory allocation for the data model acceleration process (via the limits.conf or the data model acceleration settings) directly addresses this resource constraint, allowing the summary to build successfully.
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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