The answer is to use JDBC connections with pushdown predicates and increase the number of DPUs. This combination is most effective because pushdown predicates filter data at the source database, drastically reducing the volume of rows transferred across the network to AWS Glue, while increasing DPUs allows the ETL job to process the filtered data in parallel, directly addressing both the six-hour runtime and cost concerns. On the AWS Certified Machine Learning Specialty MLS-C01 exam, this scenario tests your understanding of optimizing data ingestion for machine learning pipelines, where source bottlenecks are a common trap—many candidates mistakenly add more DPUs alone, which only overwhelms the database without pushdown filtering. A key memory tip: think of pushdown predicates as “send the WHERE clause to the database” to minimize data movement before parallel processing begins.
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 ETL jobs to process data from an Amazon RDS for MySQL database into Amazon S3. The job runs daily and takes 6 hours to complete. The team wants to reduce runtime and cost. The source table has 50 million rows and is updated continuously. Which combination of changes would be MOST effective?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Use JDBC connections with pushdown predicates and increase the number of DPUs.
Option B is correct because JDBC connections with pushdown predicates reduce data transferred, and increasing DPUs can parallelize processing. Option A is wrong because increasing DPUs without pushdown may cause bottleneck on source. Option C is wrong because a single worker cannot process 50M rows quickly. Option D is wrong because triggers do not optimize runtime.
Key principle: NAT direction and interface roles matter as much as the IP address mapping. Inside/outside designation controls which traffic is translated.
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 a single worker with a larger instance type.
Why it's wrong here
A single worker cannot scale horizontally to handle large data volumes.
✗
Increase the number of DPUs and enable job bookmarking.
Why it's wrong here
Job bookmarking helps with incremental processing but doesn't reduce initial full load.
✓
Use JDBC connections with pushdown predicates and increase the number of DPUs.
Why this is correct
Pushdown predicates filter data at source, reducing data transfer; more DPUs parallelize the work.
Related concept
Static NAT maps one inside address to one outside address.
✗
Change the job trigger from time-based to event-based.
Why it's wrong here
Trigger type does not affect job runtime.
Common exam traps
Common exam trap: NAT rules depend on direction and matching traffic
NAT is not only about the public address. The inside/outside interface roles and the ACL or rule that matches traffic are just as important.
Detailed technical explanation
How to think about this question
NAT questions usually test address translation, overload/PAT behaviour, static mappings and whether the right traffic is being translated. Read the interface direction and address terms carefully.
KKey Concepts to Remember
Static NAT maps one inside address to one outside address.
PAT allows many inside hosts to share one public address using ports.
Inside local and inside global describe the private and translated addresses.
NAT ACLs identify traffic for translation, not always security filtering.
TExam Day Tips
→Identify inside and outside interfaces first.
→Check whether the scenario needs static NAT, dynamic NAT or PAT.
→Do not confuse NAT matching ACLs with normal packet-filtering intent.
Key takeaway
NAT direction and interface roles matter as much as the IP address mapping. Inside/outside designation controls which traffic is translated.
Real-world example
How this comes up in practice
A startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.
What to study next
Got this wrong? Here's your next step.
Review the four NAT address types (inside local, inside global, outside local, outside global), PAT port overload, and static vs dynamic NAT use cases. Then practise related MLS-C01 NAT questions on configuration and troubleshooting.
Data Engineering — This question tests Data Engineering — Static NAT maps one inside address to one outside address..
What is the correct answer to this question?
The correct answer is: Use JDBC connections with pushdown predicates and increase the number of DPUs. — Option B is correct because JDBC connections with pushdown predicates reduce data transferred, and increasing DPUs can parallelize processing. Option A is wrong because increasing DPUs without pushdown may cause bottleneck on source. Option C is wrong because a single worker cannot process 50M rows quickly. Option D is wrong because triggers do not optimize runtime.
What should I do if I get this MLS-C01 question wrong?
Review the four NAT address types (inside local, inside global, outside local, outside global), PAT port overload, and static vs dynamic NAT use cases. Then practise related MLS-C01 NAT questions on configuration and troubleshooting.
What is the key concept behind this question?
Static NAT maps one inside address to one outside address.
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Question Discussion
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