MLA-C01 Data Preparation for Machine Learning Practice Question
Network Topology
Refer to the exhibit. A data engineer deploys this Glue job via CloudFormation. When running, the job fails with a timeout after 2 hours. The job processes a large dataset and expected to take 3 hours. Which change would resolve the issue?
⚠ Common exam trap
AWS often tests the distinction between performance-related fixes (increasing workers or changing worker type) versus configuration-related fixes (timeout), leading candidates to mistakenly choose options that improve speed rather than addressing the explicit timeout limit.
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
✓
Increase the Timeout property to 240 minutes
The Glue job failed due to a timeout after 2 hours, but the expected runtime is 3 hours. The default timeout for AWS Glue jobs is 2880 minutes (48 hours), but the CloudFormation template likely set a lower value. Increasing the Timeout property to 240 minutes (4 hours) provides enough time for the job to complete without being prematurely terminated.
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 NumberOfWorkers to 20
Why it's wrong here
Adding workers may reduce execution time but the immediate failure is due to the timeout limit, not performance.
- ✗
Set MaxRetries to 3
Why it's wrong here
Retries do not extend the timeout; the job will fail again after retrying with the same timeout.
- ✓
Increase the Timeout property to 240 minutes
Why this is correct
Increasing the timeout directly addresses the failure caused by the 120-minute limit.
- ✗
Change WorkerType to G.2X
Why it's wrong here
Faster workers may reduce runtime but do not change the timeout limit.
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