DEA-C01 AWS Glue Worker Types Practice Question
A data engineer notices that an AWS Glue ETL job is failing with an OutOfMemory error when processing a large dataset. The job uses a Standard worker type. Which action is MOST effective to resolve this issue without changing the job script?
⚠ Common exam trap
Candidates may think increasing the number of workers adds more memory, but it only increases parallelism. The memory per worker remains the same. Changing worker type (e.g., to G.2X) is the direct fix.
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 to G.2X worker type
The most effective action is to switch to the G.2X worker type (Option C). AWS Glue worker types determine the vCPU, memory, and disk allocated per worker. Standard and G.1X both provide 4 vCPU and 16 GB memory per worker (1 DPU); G.1X does not increase memory over Standard, only disk. G.2X doubles resources to 8 vCPU and 32 GB memory (2 DPU), directly resolving the OutOfMemory error without changing the script. Option A increases the number of workers but not per-worker memory. Option B (G.1X) does not increase memory, so it is not effective. Option D is invalid because DPUs per worker is not a configurable parameter; it is defined by the worker type.
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 the number of workers
Why it's wrong here
Increasing the number of workers does not increase memory per worker, so it may not resolve the OutOfMemory error.
- ✗
Switch to G.1X worker type
Why it's wrong here
Switching to G.1X provides 1 DPU (8 GB) per worker, more memory than Standard but less than G.2X; not the most effective option.
- ✓
Change to G.2X worker type
Why this is correct
Changing to G.2X allocates 2 DPU (16 GB) per worker, directly increasing memory and resolving the OutOfMemory error most effectively.
- ✗
Increase the number of DPUs per worker
Why it's wrong here
Increasing DPU per worker is not a configurable parameter in AWS Glue; DPU allocation is determined by the worker type. This option is invalid.
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Same concept, more angles
2 more ways this is tested on DEA-C01
These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. A data engineer needs to troubleshoot why an AWS Glue job is failing with a 'Insufficient Memory' error. The job processes a 10 GB dataset. Which step should the engineer take FIRST?
easy- A.Switch from using Apache Spark to Python shell.
- B.Repartition the data into more partitions within the job.
- C.Change the job type from Python to Java.
- ✓ D.Increase the number of DPUs allocated to the job.
Why D: The FIRST step when a Glue job fails with 'Insufficient Memory' is to increase the number of DPUs (Data Processing Units) allocated to the job. More DPUs provide more executors and memory, directly addressing the memory constraint. This is the most direct, low-risk remediation before considering code or job-type changes.
Variation 2. A data engineer notices that an AWS Glue ETL job is failing with a 'MemoryError' when processing a large dataset. Which approach should the engineer take to resolve this issue?
easy- ✓ A.Increase the number of DPUs for the job.
- B.Change the source file format from Parquet to JSON.
- C.Reduce the number of partitions in the source data.
- D.Use S3 Select to filter data before processing.
Why A: Increasing the number of DPUs allocates more memory and processing capacity, which can resolve memory errors. Option B is incorrect because changing from Parquet to JSON typically increases memory usage due to less efficient encoding. Option C is incorrect because reducing partitions may increase memory pressure per partition. Option D is incorrect because S3 Select can filter data before loading but does not directly address the memory limitation in Glue; increasing DPUs is the more direct solution.
JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This DEA-C01 practice question is part of Courseiva's free Amazon Web Services certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the DEA-C01 exam.