- A
Disable job bookmarking
Why wrong: Job bookmarking helps process only new data; disabling it may reprocess all data, increasing runtime.
- B
Increase the number of DPUs allocated to the job
More DPUs enable parallel processing, reducing runtime.
- C
Reduce the number of workers
Why wrong: Fewer workers would increase runtime.
- D
Change the job type from Spark to Python shell
Why wrong: Python shell has limited parallelism and may be slower.
- E
Partition the input data in S3
Partitioning reduces the amount of data scanned.
Question 1,294 of 1,786
DEA-C01 Data Operations and Support Practice Question
This DEA-C01 practice question tests your understanding of data operations and support. 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 is using AWS Glue to process data stored in Amazon S3. The Glue job runs successfully but takes longer than expected. Which TWO actions can reduce the job runtime?
Answer choices
Why each option matters
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 job
Option B is correct: Increasing DPUs (Data Processing Units) allocates more compute resources to the Glue job, allowing it to process data faster, thus reducing runtime. Option E is correct: Partitioning the input data in S3 allows Glue to use partition pruning, reading only the necessary partitions instead of scanning the entire dataset, which reduces I/O and processing time. Option A is incorrect: Disabling job bookmarking does not reduce runtime; it only affects how Glue tracks processed data and might cause reprocessing. Option C is incorrect: Reducing the number of workers would decrease parallelism, likely increasing runtime. Option D is incorrect: Changing from Spark to Python Shell would likely increase runtime because Python Shell is single-threaded and not designed for large-scale data processing compared to Spark.
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.
- ✗
Disable job bookmarking
Why it's wrong here
Job bookmarking helps process only new data; disabling it may reprocess all data, increasing runtime.
- ✓
Increase the number of DPUs allocated to the job
Why this is correct
More DPUs enable parallel processing, reducing runtime.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Reduce the number of workers
Why it's wrong here
Fewer workers would increase runtime.
- ✗
Change the job type from Spark to Python shell
Why it's wrong here
Python shell has limited parallelism and may be slower.
- ✓
Partition the input data in S3
Why this is correct
Partitioning reduces the amount of data scanned.
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.
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.
Quick reference
AWS S3 Storage Class Comparison
| Storage Class | Min Duration | Retrieval | Use Case |
|---|---|---|---|
| S3 Standard | None | Immediate | Frequently accessed data |
| S3 Standard-IA | 30 days | Immediate | Infrequent access, rapid retrieval |
| S3 One Zone-IA | 30 days | Immediate | Non-critical infrequent data |
| S3 Intelligent-Tiering | None | Immediate–hours | Unknown or changing access patterns |
| S3 Glacier Instant | 90 days | Milliseconds | Archive with instant retrieval |
| S3 Glacier Flexible | 90 days | Minutes–hours | Archive, flexible retrieval |
| S3 Glacier Deep Archive | 180 days | Hours | Long-term compliance archive |
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.
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FAQ
Questions learners often ask
What does this DEA-C01 question test?
Data Operations and Support — This question tests Data Operations and Support — 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 job — Option B is correct: Increasing DPUs (Data Processing Units) allocates more compute resources to the Glue job, allowing it to process data faster, thus reducing runtime. Option E is correct: Partitioning the input data in S3 allows Glue to use partition pruning, reading only the necessary partitions instead of scanning the entire dataset, which reduces I/O and processing time. Option A is incorrect: Disabling job bookmarking does not reduce runtime; it only affects how Glue tracks processed data and might cause reprocessing. Option C is incorrect: Reducing the number of workers would decrease parallelism, likely increasing runtime. Option D is incorrect: Changing from Spark to Python Shell would likely increase runtime because Python Shell is single-threaded and not designed for large-scale data processing compared to Spark.
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.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
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Last reviewed: Jun 20, 2026
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