The answer is to increase the number of DPUs allocated to the Glue job and use a larger worker type, such as G.2X or G.4X. This directly resolves memory errors in AWS Glue ETL jobs because each DPU provides a fixed amount of memory and compute, and upgrading the worker type increases the memory per worker, allowing the job to handle larger data volumes without hitting the 'MemoryError' threshold. On the AWS Certified Machine Learning Specialty MLS-C01 exam, this scenario tests your understanding of Glue job configuration for cost-effective scaling—specifically, that increasing DPUs and choosing a memory-optimized worker type is the simplest fix, whereas repartitioning or switching to a Python shell are either complex or counterproductive traps. Remember the mnemonic: "More DPUs, More Memory"—when data grows, scale up workers before tuning code.
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 is using AWS Glue to run ETL jobs that transform data from multiple sources into a data lake on S3. The jobs are scheduled to run hourly. Recently, the jobs have been failing intermittently with 'MemoryError' exceptions. The data volume has grown over time. The data engineer needs to resolve this issue cost-effectively. Which action should be taken?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Increase the number of DPUs allocated to the Glue job and use a larger worker type.
Option B is correct because Glue jobs can be configured to use more DPUs (Data Processing Units) to increase memory, and using worker type G.2X or G.4X provides more memory per worker. Option A (increasing S3 timeout) does not address memory. Option C (Spark partitioning) may help but is more complex and may not be sufficient if memory is insufficient. Option D (changing to Python shell) reduces memory and will likely fail.
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 number of DPUs allocated to the Glue job and use a larger worker type.
Why this is correct
More DPUs and larger worker types provide more memory to handle larger data volumes.
Related concept
Read the scenario before looking for a memorised answer.
✗
Increase the S3 timeout settings in the Glue job configuration.
Why it's wrong here
Timeout settings do not affect memory allocation.
✗
Switch the Glue job type from Spark to Python shell to reduce memory overhead.
Why it's wrong here
Python shell uses less memory and will likely fail on large datasets.
✗
Repartition the data using Spark's repartition method before processing.
Why it's wrong here
Repartitioning may help but may not resolve memory errors if the overall memory is insufficient.
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 startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.
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 number of DPUs allocated to the Glue job and use a larger worker type. — Option B is correct because Glue jobs can be configured to use more DPUs (Data Processing Units) to increase memory, and using worker type G.2X or G.4X provides more memory per worker. Option A (increasing S3 timeout) does not address memory. Option C (Spark partitioning) may help but is more complex and may not be sufficient if memory is insufficient. Option D (changing to Python shell) reduces memory and will likely fail.
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.
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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