DEA-C01 Data Ingestion and Transformation Practice Question
A data pipeline uses AWS Glue to process large CSV files. The team notices that some jobs fail with out-of-memory errors. Which TWO configuration changes can help mitigate 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
✓
Increase the number of DPUs for the Glue job.
Options B and C are correct: increasing the number of DPUs provides more memory, and enabling autoscaling allows the job to automatically scale resources as needed. Option A (reducing DPUs) would worsen the problem by limiting resources. Option D (converting to Parquet) can improve performance but is not a direct configuration change for the Glue job itself. Option E (job bookmarks) is for incremental processing and does 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.
- ✗
Reduce the number of DPUs to limit concurrency.
Why it's wrong here
Would reduce memory, worsening issue.
- ✓
Increase the number of DPUs for the Glue job.
Why this is correct
More DPUs provide more memory.
- ✓
Enable Glue job autoscaling.
Why this is correct
Dynamically adjusts resources to meet demand.
- ✗
Convert input files from CSV to Parquet.
Why it's wrong here
May help but is an external change, not a configuration fix.
- ✗
Enable job bookmarks.
Why it's wrong here
Does not affect memory.
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