The answer is to increase the number of workers (DPUs) for the Glue job. This is the most effective action because scaling AWS Glue ETL workers directly increases parallelism, allowing the job to process the 500 MB of input data across more distributed compute resources, which reduces runtime. Since the job reads only the latest hour’s partitioned data, adding workers avoids the overhead of repartitioning or changing execution engines, making it a straightforward resource-based optimization. On the AWS Certified Data Engineer Associate DEA-C01 exam, this scenario tests your understanding that for small, fixed-size datasets, scaling workers is often the simplest way to meet tight time windows, while common traps suggest unnecessary code changes like repartitioning or switching to Spark SQL. Remember the memory tip: “Small data, big clock? Add more DPUs to the flock.”
DEA-C01 Data Ingestion and Transformation Practice Question
This DEA-C01 practice question tests your understanding of data ingestion and transformation. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. 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 AWS Glue ETL jobs to transform data in Amazon S3. The data is partitioned by date and hour. The job reads the latest hour's data, performs aggregations, and writes results to a separate S3 bucket. The job runs every hour and processes approximately 500 MB of input data. The team notices that the job takes longer than expected, often exceeding the 1-hour window. Which action would most effectively reduce the job's runtime?
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 workers (DPUs) for the Glue job.
The correct answer is to increase the number of workers. The job processes only 500 MB, so increasing worker count (DPUs) will improve parallelism. Option B is incorrect because the job processes only one hour's data, and repartitioning would add overhead. Option C is incorrect because using Spark SQL does not inherently improve performance. Option D is incorrect because switching to a Python shell would not handle the transformation efficiently. Option A directly adds resources to speed up the job.
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.
✗
Use a Python shell job instead of a Spark job.
Why it's wrong here
Python shell jobs are for light processing and not suitable for large transformations.
✗
Switch from using DynamicFrame to using Spark SQL for transformations.
Why it's wrong here
Spark SQL may have similar performance; the bottleneck is likely resources, not API.
✗
Repartition the input data into more partitions before reading.
Why it's wrong here
Repartitioning adds overhead and does not help when reading a single partition.
✓
Increase the number of workers (DPUs) for the Glue job.
Why this is correct
More workers increase parallelism, reducing runtime for the given data size.
Related concept
Read the scenario before looking for a memorised answer.
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.
Trap categories for this question
Similar concept trap
Spark SQL may have similar performance; the bottleneck is likely resources, not API.
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 DEA-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 Ingestion and Transformation — This question tests Data Ingestion and Transformation — 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 workers (DPUs) for the Glue job. — The correct answer is to increase the number of workers. The job processes only 500 MB, so increasing worker count (DPUs) will improve parallelism. Option B is incorrect because the job processes only one hour's data, and repartitioning would add overhead. Option C is incorrect because using Spark SQL does not inherently improve performance. Option D is incorrect because switching to a Python shell would not handle the transformation efficiently. Option A directly adds resources to speed up the job.
What should I do if I get this DEA-C01 question wrong?
Identify which DEA-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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This DEA-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 DEA-C01 exam.
Question Discussion
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