- A
Increase the Redshift cluster size to 4 nodes.
Why wrong: Scaling Redshift may help but does not address the JDBC driver inefficiency.
- B
Modify the Glue job to write data to S3 first, then use the Redshift COPY command to load data.
Using COPY from S3 is the recommended approach for bulk loading into Redshift; it is faster and more reliable than JDBC writes.
- C
Increase the Glue job timeout to 24 hours.
Why wrong: Longer timeout will not fix the underlying connection issue.
- D
Use AWS Database Migration Service (DMS) to load data into Redshift.
Why wrong: DMS is for ongoing replication, not for ETL jobs.
Quick Answer
The correct answer is to modify the Glue job to write data to S3 first, then use the Redshift COPY command to load data. This resolves the connection timeout errors because the JDBC driver inserts data row-by-row, which becomes unreliable for bulk loads of 50 GB, whereas the COPY command leverages Redshift’s massively parallel processing to load data in batches directly from S3, avoiding driver bottlenecks. On the AWS Certified Machine Learning Specialty MLS-C01 exam, this scenario tests your understanding of Redshift’s native ingestion patterns versus generic JDBC connections, often appearing as a trap where candidates mistakenly scale the cluster or increase timeouts instead of switching to the optimized COPY workflow. Remember the key distinction: JDBC is for small, transactional inserts; COPY is for bulk, reliable loading. A useful memory tip is “COPY from S3, not JDBC for big loads.”
MLS-C01 Data Engineering Practice Question
This MLS-C01 practice question tests your understanding of data engineering. 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 company uses AWS Glue to run ETL jobs that transform data from Amazon S3 to Amazon Redshift. The Glue job writes data to Redshift using the JDBC connection. Recently, the job has been failing with connection timeout errors when writing to Redshift. The Redshift cluster is a 2-node dc2.large cluster. The Glue job processes about 50 GB of data per run. The errors occur sporadically, and the job succeeds after a few retries. The data engineer needs to resolve the issue to prevent job failures. What should the engineer do?
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
Modify the Glue job to write data to S3 first, then use the Redshift COPY command to load data.
Option C is correct. The Glue JDBC driver may not handle large data volumes efficiently; using the COPY command via S3 is optimized for bulk loads and is more reliable. Option A is wrong because increasing timeout may mask the issue but not resolve it. Option B is wrong because the Redshift cluster may be undersized, but the issue is likely the JDBC driver. Option D is wrong because AWS DMS is for database migration, not ETL jobs.
Key principle: Count usable hosts — not total addresses — and remember that the network and broadcast addresses are not available to hosts in standard IPv4 subnets.
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 Redshift cluster size to 4 nodes.
Why it's wrong here
Scaling Redshift may help but does not address the JDBC driver inefficiency.
- ✓
Modify the Glue job to write data to S3 first, then use the Redshift COPY command to load data.
Why this is correct
Using COPY from S3 is the recommended approach for bulk loading into Redshift; it is faster and more reliable than JDBC writes.
Related concept
CIDR notation defines the prefix length.
- ✗
Increase the Glue job timeout to 24 hours.
Why it's wrong here
Longer timeout will not fix the underlying connection issue.
- ✗
Use AWS Database Migration Service (DMS) to load data into Redshift.
Why it's wrong here
DMS is for ongoing replication, not for ETL jobs.
Common exam traps
Common exam trap: usable hosts are not the same as total addresses
Subnetting questions often tempt you into counting all addresses. In normal IPv4 subnets, the network and broadcast addresses are not usable host addresses.
Detailed technical explanation
How to think about this question
Subnetting questions test whether you can identify the network, broadcast address, usable range, mask and correct subnet. Slow down enough to calculate the block size correctly.
KKey Concepts to Remember
- CIDR notation defines the prefix length.
- Block size helps identify subnet boundaries.
- Network and broadcast addresses are not usable hosts in normal IPv4 subnets.
- The required host count determines the smallest suitable subnet.
TExam Day Tips
- Write the block size before choosing the subnet.
- Check whether the question asks for hosts, subnets or a specific address range.
- Do not confuse /24, /25, /26 and /27 host counts.
Key takeaway
Count usable hosts — not total addresses — and remember that the network and broadcast addresses are not available to hosts in standard IPv4 subnets.
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.
Review block sizes, usable host formulas (2^n − 2), and how to find network and broadcast addresses for /24 through /30. Then practise related MLS-C01 subnetting questions on CIDR, address ranges, and subnet selection.
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FAQ
Questions learners often ask
What does this MLS-C01 question test?
Data Engineering — This question tests Data Engineering — CIDR notation defines the prefix length..
What is the correct answer to this question?
The correct answer is: Modify the Glue job to write data to S3 first, then use the Redshift COPY command to load data. — Option C is correct. The Glue JDBC driver may not handle large data volumes efficiently; using the COPY command via S3 is optimized for bulk loads and is more reliable. Option A is wrong because increasing timeout may mask the issue but not resolve it. Option B is wrong because the Redshift cluster may be undersized, but the issue is likely the JDBC driver. Option D is wrong because AWS DMS is for database migration, not ETL jobs.
What should I do if I get this MLS-C01 question wrong?
Review block sizes, usable host formulas (2^n − 2), and how to find network and broadcast addresses for /24 through /30. Then practise related MLS-C01 subnetting questions on CIDR, address ranges, and subnet selection.
What is the key concept behind this question?
CIDR notation defines the prefix length.
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Last reviewed: Jun 20, 2026
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