The correct answer is to increase the spark.executor.memoryOverhead setting. This parameter allocates additional memory beyond the executor heap for JVM internals, such as thread stacks, garbage collection metadata, and off-heap storage, which is precisely where OutOfMemoryError occurs when Spark tasks exceed the default overhead limit. On the AWS Certified Machine Learning Specialty MLS-C01 exam, this question tests your understanding of Spark memory management on Amazon EMR, often trapping candidates who confuse parallelism fixes (like increasing cores) with memory allocation issues. A common mistake is to assume that reducing shuffle partitions or changing serialization will directly resolve executor crashes, but those address data movement or storage efficiency, not the immediate lack of off-heap memory. Remember the mnemonic: “Overhead is overhead—when executors crash off-heap, boost the overhead heap.”
MLS-C01 Data Engineering Practice Question
This MLS-C01 practice question tests your understanding of data engineering. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. 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 company uses Amazon EMR to run Spark jobs on a large dataset stored in Amazon S3. The jobs are failing with 'OutOfMemoryError' in the executors. The data is not skewed. Which configuration change will most likely resolve the issue?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue: "most likely"
Why it matters: Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Increase the spark.executor.memoryOverhead setting
Increasing the executor memory overhead provides additional memory for JVM overhead and can prevent OutOfMemoryError. Option A (increasing cores) may increase parallelism but not memory. Option B (decreasing shuffle partitions) may reduce memory usage but is not a direct fix. Option D (using Kryo serialization) reduces memory usage but is not as effective as increasing overhead.
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.
✗
Enable Kryo serialization
Why it's wrong here
Kryo reduces memory usage but may not be sufficient to resolve OOM if memory overhead is too low.
✗
Decrease the number of shuffle partitions
Why it's wrong here
Fewer partitions reduce memory usage but may cause data skew and does not directly address OOM.
✓
Increase the spark.executor.memoryOverhead setting
The clue word "most likely" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
✗
Increase the number of executor cores
Why it's wrong here
More cores can increase parallelism but not memory per executor.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Detailed technical explanation
How to think about this question
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
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.
Use explanations to understand the rule behind the answer.
TExam Day Tips
→Underline the problem statement mentally.
→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 media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
What to study next
Got this wrong? Here's your next step.
Identify which MLS-C01 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
Data Engineering — This question tests Data Engineering — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Increase the spark.executor.memoryOverhead setting — Increasing the executor memory overhead provides additional memory for JVM overhead and can prevent OutOfMemoryError. Option A (increasing cores) may increase parallelism but not memory. Option B (decreasing shuffle partitions) may reduce memory usage but is not a direct fix. Option D (using Kryo serialization) reduces memory usage but is not as effective as increasing overhead.
What should I do if I get this MLS-C01 question wrong?
Identify which MLS-C01 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
Are there clue words in this question I should notice?
Yes — watch for: "most likely". Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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This MLS-C01 practice question is part of Courseiva's free Amazon Web Services 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 MLS-C01 exam.
Question Discussion
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