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Question 150 of 1,786

Data Operations and Support →hardMultiple ChoiceObjective-mapped

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.

A
Use Redshift Spectrum to query data directly from S3
Why wrong: Spectrum is for querying external data, not for unloading; the job writes to S3, not reads.
B
Use the S3 staging option in the Glue connection to unload data from Redshift to S3 first
UNLOAD is parallel and faster than JDBC; Glue can then read from S3.
C
Increase the Redshift cluster size to 8 nodes
Why wrong: More nodes increase scan throughput but JDBC still serializes; UNLOAD is more effective.
D
Increase the number of Glue workers to 20
Why wrong: More workers may not help if the read from Redshift via JDBC is the bottleneck.

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

✓

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.

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.

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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: 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.

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