The correct answer is to use job bookmarks, pushdown predicates, and larger worker types. Job bookmarks enable incremental processing by tracking previously processed data, so only new or changed records are read from Amazon RDS, drastically reducing runtime. Pushdown predicates filter data at the source using SQL-like conditions in the JDBC connection, minimizing the volume of data transferred across the network and into the Glue transformation phase. Larger worker types like G.1X or G.2X provide more memory and CPU per worker, allowing each task to handle larger datasets without increasing the total number of DPUs inefficiently. On the MLS-C01 exam, this question tests your understanding of cost-effective ETL optimization—a common trap is assuming that adding more partitions after loading data speeds up processing, which it does not, or that simply increasing DPUs is always best. Remember the mnemonic “Filter, Track, Scale”: pushdown predicates filter early, bookmarks track progress, and larger workers scale compute per unit.
MLS-C01 Data Engineering Practice Question
This MLS-C01 practice question tests your understanding of data engineering. 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 company uses AWS Glue to run ETL jobs on a daily basis. The jobs read from Amazon RDS and write to Amazon S3. The data volume has grown, and the jobs are taking longer to complete. The team wants to optimize the jobs for cost and performance. Which combination of techniques should the team implement? (Choose THREE.)
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Use a larger Glue worker type, such as G.2X, for more memory per worker.
Option A, B, and D are correct. Using job bookmarks enables incremental processing, reducing the amount of data read. Using pushdown predicates filters data at the source, reducing data transfer. Using a larger number of worker type (e.g., G.1X or G.2X) increases memory and CPU per worker, improving performance. Option C is wrong because adding more partitions after the job does not speed up the job. Option E is wrong because increasing the number of DPUs increases cost linearly and may not be as effective as using larger workers.
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 larger Glue worker type, such as G.2X, for more memory per worker.
Why this is correct
Larger workers provide more resources per task, improving performance.
Related concept
Static NAT maps one inside address to one outside address.
✓
Enable job bookmarks to process only new data since the last run.
Why this is correct
Job bookmarks allow incremental processing, reducing the data volume.
Related concept
Static NAT maps one inside address to one outside address.
✗
Increase the number of partitions in the output S3 data to improve parallelism.
Why it's wrong here
Output partitions do not affect the job's processing time.
✗
Increase the maximum number of DPUs for the job to 100.
Why it's wrong here
Increasing DPUs increases cost and may not improve performance if the bottleneck is memory.
✓
Use pushdown predicates in the JDBC connection to filter data at the source.
Why this is correct
Pushdown predicates reduce the amount of data read from the database.
Related concept
Static NAT maps one inside address to one outside address.
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.
Trap categories for this question
Command / output trap
Output partitions do not affect the job's processing time.
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 a larger Glue worker type, such as G.2X, for more memory per worker. — Option A, B, and D are correct. Using job bookmarks enables incremental processing, reducing the amount of data read. Using pushdown predicates filters data at the source, reducing data transfer. Using a larger number of worker type (e.g., G.1X or G.2X) increases memory and CPU per worker, improving performance. Option C is wrong because adding more partitions after the job does not speed up the job. Option E is wrong because increasing the number of DPUs increases cost linearly and may not be as effective as using larger workers.
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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