DEA-C01 Data Ingestion and Transformation Practice Question
Network Topology
A data engineer reviews the Glue job configuration. The job fails when processing large datasets. The error message indicates out-of-memory in the executors. Which change to the job configuration will most directly address this issue?
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
✓
Change the worker type from Standard to G.2X.
The job fails due to out-of-memory errors in the executors. The current configuration uses 5 Standard workers, each with 16 GB of memory. Changing the worker type to G.2X provides 32 GB per worker, doubling the memory per executor and directly addressing the OOM issue. Increasing the number of workers (option C) adds more executors but does not increase memory per executor, which may not resolve the issue if each executor still runs out of memory. Options B and D do not affect memory.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Change the worker type from Standard to G.2X.
Why this is correct
G.2X workers have more memory (8 GB vs 4 GB), directly addressing OOM.
- ✗
Increase the timeout from 30 to 60 minutes.
Why it's wrong here
Timeout does not affect memory.
- ✗
Increase the number of workers from 5 to 10.
Why it's wrong here
More workers may help parallelism but each worker still has the same memory; the root issue is per-worker memory.
- ✗
Set MaxRetries to 3.
Why it's wrong here
Retries don't fix the memory issue.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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