- A
An AWS Glue ETL job with a Spark script.
The job performs the defined ETL logic.
- B
An AWS Glue crawler to populate the Data Catalog.
Why wrong: Crawler is not required for the ETL job; schema can be defined manually.
- C
An AWS Glue connection to the RDS database.
Connection enables Glue to access the database.
- D
An AWS Glue development endpoint.
Why wrong: Development endpoint is for development, not production.
- E
An AWS Glue notebook for data exploration.
Why wrong: Notebook is for exploration, not production scheduling.
Question 682 of 1,755
MLS-C01 Data Engineering Practice Question
This MLS-C01 practice question tests your understanding of data engineering. 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 data engineering team needs to schedule a nightly ETL job that extracts data from an Amazon RDS for PostgreSQL instance, transforms it using Spark, and loads it into Amazon S3. The team wants to use AWS Glue for this task. Which components are required? (Select TWO.)
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
✓
An AWS Glue ETL job with a Spark script.
An AWS Glue ETL job with a Spark script is required because the transformation step explicitly uses Spark. AWS Glue provides a managed Spark runtime, and the ETL job definition must include a script (either auto-generated or custom) that performs the extract, transform, and load operations. Without this component, the team cannot execute the Spark-based transformation logic.
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.
- ✓
An AWS Glue ETL job with a Spark script.
Why this is correct
The job performs the defined ETL logic.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
An AWS Glue crawler to populate the Data Catalog.
Why it's wrong here
Crawler is not required for the ETL job; schema can be defined manually.
- ✓
An AWS Glue connection to the RDS database.
Why this is correct
Connection enables Glue to access the database.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
An AWS Glue development endpoint.
Why it's wrong here
Development endpoint is for development, not production.
- ✗
An AWS Glue notebook for data exploration.
Why it's wrong here
Notebook is for exploration, not production scheduling.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often assume a crawler is mandatory for any Glue workflow, but the Data Catalog is only needed if you want to use it for schema discovery or as a metastore—the ETL job can operate without it by directly referencing the connection and writing raw data to S3.
Detailed technical explanation
How to think about this question
Under the hood, the AWS Glue connection stores JDBC connection details (e.g., host, port, database name, credentials) and uses SSL/TLS to securely connect to the RDS PostgreSQL instance. The Spark script in the Glue ETL job reads data via JDBC, applies transformations in memory using DataFrames, and writes the output to S3 in formats like Parquet or ORC. A real-world scenario where this matters is when the RDS database has a large dataset—Glue's Spark engine can parallelize reads using partition predicates to avoid overwhelming the source.
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.
Quick reference
AWS S3 Storage Class Comparison
| Storage Class | Min Duration | Retrieval | Use Case |
|---|---|---|---|
| S3 Standard | None | Immediate | Frequently accessed data |
| S3 Standard-IA | 30 days | Immediate | Infrequent access, rapid retrieval |
| S3 One Zone-IA | 30 days | Immediate | Non-critical infrequent data |
| S3 Intelligent-Tiering | None | Immediate–hours | Unknown or changing access patterns |
| S3 Glacier Instant | 90 days | Milliseconds | Archive with instant retrieval |
| S3 Glacier Flexible | 90 days | Minutes–hours | Archive, flexible retrieval |
| S3 Glacier Deep Archive | 180 days | Hours | Long-term compliance archive |
What to study next
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FAQ
Questions learners often ask
What does this MLS-C01 question test?
Data Engineering — This question tests Data Engineering — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: An AWS Glue ETL job with a Spark script. — An AWS Glue ETL job with a Spark script is required because the transformation step explicitly uses Spark. AWS Glue provides a managed Spark runtime, and the ETL job definition must include a script (either auto-generated or custom) that performs the extract, transform, and load operations. Without this component, the team cannot execute the Spark-based transformation logic.
What should I do if I get this MLS-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.
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Last reviewed: Jul 4, 2026
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