← DEA-C01·Amazon Web Services

Question 1,524 of 1,786

Data Ingestion and Transformation →hardMultiple ChoiceObjective-mapped

DEA-C01 Data Ingestion and Transformation Practice Question

This DEA-C01 practice question tests your understanding of data ingestion and transformation. 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 data engineer is troubleshooting a slow AWS Glue ETL job that reads from Amazon S3 and writes to Amazon Redshift. The job processes 10 GB of CSV data. The engineer notices that the job runs with a single DPU and takes longer than expected. Which change would MOST likely improve performance?

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.

A
Replace Redshift with Amazon Redshift Spectrum.
Why wrong: Spectrum queries data in S3, but the job is ETL, not ad-hoc querying.
B
Change the input format to Parquet and enable predicate pushdown.
Why wrong: While Parquet can help, the primary bottleneck is likely the single DPU.
C
Use a JDBC connection to read data directly from S3.
Why wrong: JDBC is for databases, not S3.
D
Increase the number of DPUs and configure the job to use the S3 list implementation for parallel reads.
More DPUs allow parallel processing, and S3 list implementation improves file discovery.

Full breakdown with real-world context →

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 and configure the job to use the S3 list implementation for parallel reads.

The job runs with a single DPU, which limits parallelism. Increasing the number of DPUs allows the job to process data in parallel across multiple workers. Additionally, configuring the S3 list implementation enables the job to list objects in parallel, reducing the overhead of discovering input files. This combination directly addresses the bottleneck of a single-threaded read from S3.

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.

✗
Replace Redshift with Amazon Redshift Spectrum.
Why it's wrong here
Spectrum queries data in S3, but the job is ETL, not ad-hoc querying.
✗
Change the input format to Parquet and enable predicate pushdown.
Why it's wrong here
While Parquet can help, the primary bottleneck is likely the single DPU.
✗
Use a JDBC connection to read data directly from S3.
Why it's wrong here
JDBC is for databases, not S3.
✓
Increase the number of DPUs and configure the job to use the S3 list implementation for parallel reads.
Why this is correct
More DPUs allow parallel processing, and S3 list implementation improves file discovery.
Clue confirmation
The clue word "most likely" 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 that candidates often focus on data format optimization (Parquet) or query engine changes (Redshift Spectrum) without realizing that the primary bottleneck is the single-DPU configuration limiting parallelism, which is a common oversight in Glue job tuning questions.

Detailed technical explanation

How to think about this question

AWS Glue ETL jobs allocate DPUs (Data Processing Units) where each DPU provides 4 vCPUs and 16 GB of memory. With a single DPU, the job is limited to one executor, causing sequential processing of S3 partitions. The S3 list implementation (e.g., using the S3 paginator or the `boto3` list_objects_v2 with multiple threads) allows the Spark driver to discover input files in parallel, reducing the time spent in the listing phase. In practice, for 10 GB of CSV data, increasing DPUs to 5-10 and enabling parallel listing can reduce job duration by 5-10x.

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.

Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.

Related DEA-C01 practice-question pages

Use these pages to review the topic behind this question. This is how one missed question becomes focused revision.

Data Ingestion and Transformation practice questions

Practise DEA-C01 questions linked to Data Ingestion and Transformation.

Data Operations and Support practice questions

Practise DEA-C01 questions linked to Data Operations and Support.

Data Security and Governance practice questions

Practise DEA-C01 questions linked to Data Security and Governance.

Data Store Management practice questions

Practise DEA-C01 questions linked to Data Store Management.

DEA-C01 fundamentals practice questions

Practise DEA-C01 questions linked to DEA-C01 fundamentals.

DEA-C01 scenario practice questions

Practise DEA-C01 questions linked to DEA-C01 scenario.

DEA-C01 troubleshooting practice questions

Practise DEA-C01 questions linked to DEA-C01 troubleshooting.

Practice this exam

Start a free DEA-C01 practice session

Short sessions build daily habit. Longer sessions build exam-day stamina. Try a timed session to simulate real conditions.

10 questions 20 questions 30 questions 50 questions Timed 30

DEA-C01 practice-test guide →Study guide →Browse all practice tests

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: Increase the number of DPUs and configure the job to use the S3 list implementation for parallel reads. — The job runs with a single DPU, which limits parallelism. Increasing the number of DPUs allows the job to process data in parallel across multiple workers. Additionally, configuring the S3 list implementation enables the job to list objects in parallel, reducing the overhead of discovering input files. This combination directly addresses the bottleneck of a single-threaded read from S3.

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: "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.

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 →

How Courseiva writes practice questions · Editorial policy

Keep practising

Question Discussion

Share a tip, memory trick, or ask about the reasoning behind this question. Do not post real exam questions, leaked content, braindumps, or copyrighted exam material. Comments are moderated and may be removed without notice.

Loading comments…

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.