The answer is to use the S3 staging option in the Glue connection to unload data from Redshift to S3 first. This is correct because a standard JDBC connection reads data row-by-row from Redshift, creating a severe bottleneck for large datasets, whereas the S3 staging option leverages Redshift’s UNLOAD command to export data in parallel directly to S3, taking full advantage of Redshift’s massively parallel processing (MPP) architecture. On the AWS Certified Data Engineer Associate DEA-C01 exam, this question tests your understanding of optimizing Glue ETL from Redshift using S3 staging, a common performance pattern that avoids slow JDBC reads. A frequent trap is assuming that simply increasing Glue workers or upgrading Redshift nodes will fix the issue, but the real bottleneck is the row-by-row JDBC transfer. Remember the memory tip: “Unload, don’t unroll” — use UNLOAD to S3 instead of rolling through rows with JDBC.
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 data team runs a daily AWS Glue ETL job that processes data from an Amazon Redshift cluster and writes results to Amazon S3. The job completes successfully but takes 2 hours longer than expected. The job uses the JDBC connection to Redshift. The Redshift cluster is 4 dc2.large nodes. The Glue job has 10 workers of type G.1X. Which change would MOST likely reduce the job duration?
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.
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Use the S3 staging option in the Glue connection to unload data from Redshift to S3 first
The JDBC connection in AWS Glue reads data row-by-row from Redshift, which is slow for large datasets. By enabling the S3 staging option in the Glue connection, the job uses Redshift's UNLOAD command to export data to S3 in parallel, then Glue reads from S3. This bypasses the JDBC bottleneck and leverages Redshift's massively parallel processing (MPP) to export data much faster.
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 Redshift Spectrum to query data directly from S3
Why it's wrong here
Spectrum is for querying external data, not for unloading; the job writes to S3, not reads.
✓
Use the S3 staging option in the Glue connection to unload data from Redshift to S3 first
Why this is correct
UNLOAD is parallel and faster than JDBC; Glue can then read from S3.
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.
✗
Increase the Redshift cluster size to 8 nodes
Why it's wrong here
More nodes increase scan throughput but JDBC still serializes; UNLOAD is more effective.
✗
Increase the number of Glue workers to 20
Why it's wrong here
More workers may not help if the read from Redshift via JDBC is the bottleneck.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates assume the bottleneck is either Redshift compute (C) or Glue parallelism (D), when in fact the JDBC driver's single-threaded row-by-row fetch is the primary performance limiter.
Detailed technical explanation
How to think about this question
The S3 staging option internally executes a Redshift UNLOAD command, which writes data in parallel to S3 as compressed, columnar files (e.g., Parquet). Glue then reads these files using its native S3 connector, which supports partitioning and parallel reads. This approach can reduce extraction time by orders of magnitude compared to JDBC, especially for large tables, as UNLOAD leverages all Redshift slices simultaneously.
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.
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.
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: Use the S3 staging option in the Glue connection to unload data from Redshift to S3 first — The JDBC connection in AWS Glue reads data row-by-row from Redshift, which is slow for large datasets. By enabling the S3 staging option in the Glue connection, the job uses Redshift's UNLOAD command to export data to S3 in parallel, then Glue reads from S3. This bypasses the JDBC bottleneck and leverages Redshift's massively parallel processing (MPP) to export data much faster.
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 →
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.
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
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.
Sign in to join the discussion.