- A
Increase the Glue job's batch window to 600 seconds.
Why wrong: Increasing batch window delays job start.
- B
Increase the number of DPUs for the Glue job to accelerate processing.
Why wrong: This helps processing speed but not start latency.
- C
Pre-process the files to consolidate them into larger files before the Glue job runs.
Fewer larger files reduce Glue job overhead and improve throughput.
- D
Use Amazon S3 event notifications to trigger an AWS Lambda function that starts the Glue job upon file arrival.
Event-driven invocation reduces latency compared to scheduled runs.
Question 1,711 of 1,786
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 is running a critical application that generates millions of small JSON files every hour in an S3 bucket. A data engineer needs to process these files in near real-time using AWS Glue. The engineer wants to minimize the latency between file arrival and Glue job start. Which TWO actions should the engineer take?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue:
"minimum / minimize"Why it matters: Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.
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
✓
Pre-process the files to consolidate them into larger files before the Glue job runs.
Option C is correct because consolidating millions of small JSON files into larger files reduces the overhead of S3 LIST operations and minimizes the number of partitions Glue must scan. This directly lowers the latency between file arrival and job start, as Glue jobs are more efficient when processing fewer, larger files rather than many small files. Option D is correct because S3 event notifications can trigger a Lambda function that immediately starts the Glue job upon file arrival, enabling near real-time processing without polling or scheduled delays.
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 Glue job's batch window to 600 seconds.
Why it's wrong here
Increasing batch window delays job start.
- ✗
Increase the number of DPUs for the Glue job to accelerate processing.
Why it's wrong here
This helps processing speed but not start latency.
- ✓
Pre-process the files to consolidate them into larger files before the Glue job runs.
Why this is correct
Fewer larger files reduce Glue job overhead and improve throughput.
Clue confirmation
The clue word "minimum / minimize" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
- ✓
Use Amazon S3 event notifications to trigger an AWS Lambda function that starts the Glue job upon file arrival.
Why this is correct
Event-driven invocation reduces latency compared to scheduled runs.
Clue confirmation
The clue word "minimum / minimize" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is confusing job startup latency with job execution speed — candidates often choose DPU increases (Option B) thinking they reduce latency, but DPUs only affect processing speed after the job starts, not the time to initiate the job.
Detailed technical explanation
How to think about this question
Under the hood, AWS Glue uses Apache Spark, which incurs significant overhead when processing many small files due to task scheduling and metadata operations. Consolidating files reduces the number of Spark partitions and minimizes S3 LIST API calls, which are throttled at 5,500 requests per second per prefix. S3 event notifications use SQS or Lambda to trigger actions within seconds, making them ideal for near real-time pipelines.
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 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.
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FAQ
Questions learners often ask
What does this DEA-C01 question test?
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: Pre-process the files to consolidate them into larger files before the Glue job runs. — Option C is correct because consolidating millions of small JSON files into larger files reduces the overhead of S3 LIST operations and minimizes the number of partitions Glue must scan. This directly lowers the latency between file arrival and job start, as Glue jobs are more efficient when processing fewer, larger files rather than many small files. Option D is correct because S3 event notifications can trigger a Lambda function that immediately starts the Glue job upon file arrival, enabling near real-time processing without polling or scheduled delays.
What should I do if I get this DEA-C01 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: "minimum / minimize". Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
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Last reviewed: Jul 4, 2026
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