The correct answer is to increase the number of DPUs allocated to the Glue job. An out of memory error in AWS Glue streaming jobs occurs when the processing workload exceeds the available memory and compute capacity of the current worker configuration, causing the Spark executor to fail. By increasing the number of Data Processing Units (DPUs), you horizontally scale the job’s resources, directly providing more memory to handle the streaming data volume from Kinesis and the transformation overhead of converting JSON to Parquet. On the AWS Certified Data Engineer Associate DEA-C01 exam, this scenario tests your understanding of Glue job resource tuning versus code-level fixes—a common trap is trying to optimize the script or reduce batch size when the real issue is insufficient DPUs. Remember the memory tip: “OOM? Boost the DPU count—more workers, more memory, no more errors.”
DEA-C01 Data Ingestion and Transformation Practice Question
This DEA-C01 practice question tests your understanding of data ingestion and transformation. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. 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 process streaming data from Amazon Kinesis Data Streams. The job reads JSON records and writes Parquet to Amazon S3. Recently, the job started failing with 'Out of Memory' errors. Which change is MOST likely to resolve the issue?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue: "most likely"
Why it matters: Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
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 allocated to the Glue job.
The 'Out of Memory' error in AWS Glue indicates that the job's allocated resources are insufficient for the data volume or processing complexity. Increasing the number of DPUs (Data Processing Units) directly increases the available memory and compute capacity, which is the most straightforward fix for OOM errors in Glue streaming jobs. Option C is correct because it addresses the root cause—resource exhaustion—by scaling the job horizontally.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
✗
Enable compression on the Kinesis stream.
Why it's wrong here
Compression on Kinesis does not affect Glue memory.
✗
Change the output format from Parquet to ORC.
Why it's wrong here
ORC is similar to Parquet; format change does not fix OOM.
✓
Increase the number of DPUs allocated to the Glue job.
Why this is correct
More DPUs provide more memory and CPU.
Clue confirmation
The clue word "most likely" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
✗
Reduce the streaming batch size in the Glue job configuration.
Why it's wrong here
Reducing batch size can help but does not address the root cause of insufficient memory.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse 'Out of Memory' with a data format or compression issue, leading them to choose options like A or B, when the real solution is to scale compute resources via DPUs.
Trap categories for this question
Similar concept trap
ORC is similar to Parquet; format change does not fix OOM.
Detailed technical explanation
How to think about this question
AWS Glue streaming jobs use a fixed number of DPUs (default 10) where each DPU provides 4 vCPU and 16 GB of memory. When processing high-throughput Kinesis streams or complex transformations (e.g., nested JSON parsing, schema inference), memory can be exhausted if the batch size or record complexity exceeds the heap. Increasing DPUs scales memory linearly, but note that Glue streaming jobs also have a maximum of 100 DPUs, and over-allocating can lead to unnecessary cost without improving performance if the bottleneck is not memory.
KKey Concepts to Remember
Read the scenario before looking for a memorised answer.
Find the constraint that changes the correct option.
Eliminate answers that are true in general but not in this case.
TExam Day Tips
→Watch for words such as best, first, most likely and least administrative effort.
→Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Data Ingestion and Transformation — This question tests Data Ingestion and Transformation — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Increase the number of DPUs allocated to the Glue job. — The 'Out of Memory' error in AWS Glue indicates that the job's allocated resources are insufficient for the data volume or processing complexity. Increasing the number of DPUs (Data Processing Units) directly increases the available memory and compute capacity, which is the most straightforward fix for OOM errors in Glue streaming jobs. Option C is correct because it addresses the root cause—resource exhaustion—by scaling the job horizontally.
What should I do if I get this DEA-C01 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Are there clue words in this question I should notice?
Yes — watch for: "most likely". Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
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 company uses AWS Glue to process streaming data from Amazon Kinesis Data Streams. The job fails intermittently with a 'MemoryError'. What is the MOST likely cause?
medium
✓ A.The Glue job worker type is too small for the data volume
B.The Glue job uses too many DynamicFrames
C.The S3 output bucket is in a different region
D.The Kinesis stream has insufficient shards
Why A: The error suggests the job runs out of memory. Increasing the DPU count can allocate more memory per worker and help process larger data volumes without memory errors.
Variation 2. A company is using AWS Glue to process streaming data from Amazon Kinesis Data Streams. The job fails intermittently with a 'MemoryError' when the stream has a sudden spike in data volume. Which configuration change would best prevent this error?
medium
✓ A.Increase the number of DPUs (Data Processing Units) for the Glue job.
B.Store intermediate results in Amazon RDS.
C.Use a batch transformation instead of streaming.
D.Increase the number of shards in the Kinesis data stream.
Why A: Option A is correct because increasing the number of DPUs in the AWS Glue job provides more memory for processing spikes. Option B is wrong because Kinesis shard count affects throughput, not memory. Option C is wrong because batch processing does not help streaming jobs. Option D is wrong because RDS is unrelated to Glue memory.
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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.
Question Discussion
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