- A
Amazon S3 Select
Why wrong: S3 Select retrieves subsets of data, does not convert format.
- B
Amazon EMR
Why wrong: EMR requires provisioning and managing clusters.
- C
AWS Lambda
Why wrong: Lambda is not designed for large-scale ETL; time and memory limits apply.
- D
AWS Glue
Glue provides serverless Spark jobs for format conversion.
Question 305 of 1,000
Serverless CSV and JSON to Parquet Conversion Using AWS Glue
This MLA-C01 practice question tests your understanding of data preparation for machine learning. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. 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.
An ML engineer needs to convert a raw dataset from CSV to Parquet format in a serverless manner for cost efficiency. Which AWS service can be used to perform this conversion without managing servers?
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
✓
AWS Glue
AWS Glue is correct because it provides a serverless ETL service that can automatically convert CSV to Parquet using its built-in transform capabilities, such as the `ChangeSchema` or `ConvertToParquet` transforms in a Glue ETL job. This eliminates the need to provision or manage any servers, aligning with the cost-efficiency requirement.
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.
- ✗
Amazon S3 Select
Why it's wrong here
S3 Select retrieves subsets of data, does not convert format.
- ✗
Amazon EMR
Why it's wrong here
EMR requires provisioning and managing clusters.
- ✗
AWS Lambda
Why it's wrong here
Lambda is not designed for large-scale ETL; time and memory limits apply.
- ✓
AWS Glue
Why this is correct
Glue provides serverless Spark jobs for format conversion.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse AWS Glue's serverless ETL capability with Amazon EMR's managed clusters, assuming EMR is also serverless, but EMR requires explicit cluster management and is not truly serverless like Glue.
Detailed technical explanation
How to think about this question
Under the hood, AWS Glue uses Apache Spark as its execution engine, and the Parquet conversion leverages Spark's optimized columnar storage format, which reduces I/O and improves compression compared to row-based CSV. A subtle behavior is that Glue's DynamicFrame automatically infers schema from CSV, but you must handle data types carefully (e.g., timestamps) to avoid schema mismatch errors during conversion. In real-world scenarios, this is critical for ML pipelines where Parquet's predicate pushdown can significantly speed up subsequent data loading for training.
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 startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.
Quick reference
Cloud Service Model Comparison
| Model | You Manage | Provider Manages | Examples |
|---|---|---|---|
| IaaS | OS, runtime, apps, data | Hardware, hypervisor, networking | EC2, Azure VMs, GCP Compute Engine |
| PaaS | Apps and data | OS, runtime, middleware, hardware | Elastic Beanstalk, Azure App Service |
| SaaS | Data and settings only | Everything else | Microsoft 365, Salesforce, Workday |
| FaaS / Serverless | Function code only | Infra, scaling, runtime | Lambda, Azure Functions, Cloud Run |
| CaaS | Containers and apps | Kubernetes, OS, hardware | EKS, AKS, GKE |
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.
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FAQ
Questions learners often ask
What does this MLA-C01 question test?
Data Preparation for Machine Learning — This question tests Data Preparation for Machine Learning — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: AWS Glue — AWS Glue is correct because it provides a serverless ETL service that can automatically convert CSV to Parquet using its built-in transform capabilities, such as the `ChangeSchema` or `ConvertToParquet` transforms in a Glue ETL job. This eliminates the need to provision or manage any servers, aligning with the cost-efficiency requirement.
What should I do if I get this MLA-C01 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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 →
Same concept, more angles
1 more ways this is tested on MLA-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 convert a JSON dataset to Parquet format for efficient querying with Amazon Athena. The JSON files are in an S3 bucket. Which service can perform this conversion with minimal coding?
easy- A.Amazon SageMaker Processing
- B.Amazon EMR
- C.AWS Lambda
- ✓ D.AWS Glue Studio with a visual job
Why D: AWS Glue Studio with a visual job is the correct choice because it provides a no-code, drag-and-drop interface to create ETL jobs that can read JSON from S3 and write it as Parquet, with built-in schema inference and transformation capabilities. This minimizes coding effort while leveraging Glue's serverless Spark engine for efficient conversion, making it ideal for preparing data for Athena queries.
Keep practising
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Last reviewed: Jun 24, 2026
This MLA-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 MLA-C01 exam.
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