MLS-C01 Data Engineering Practice Question
A team is building a data pipeline to process terabytes of log data daily using Amazon EMR. The data arrives in 5-minute windows and must be available for querying within 30 minutes. The data is originally in gzip-compressed CSV files. Which approach will minimize processing time and cost?
⚠ Common exam trap
The trap here is that candidates may overlook the cost savings of spot instances for transient, fault-tolerant workloads, or assume that any compression (like gzip CSV) is sufficient for performance, ignoring the benefits of columnar formats like Parquet for analytical queries.
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
✓
Use Amazon EMR with Spark to convert data to Parquet and store in S3, using spot instances for task nodes.
Converting gzip-compressed CSV to Parquet reduces storage size and improves query performance due to columnar storage and predicate pushdown. Using spot instances for task nodes significantly lowers compute cost, while the 30-minute SLA is achievable with Spark on EMR processing 5-minute windows of data.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Use Amazon EMR with Spark to convert data to Parquet and use on-demand instances.
Why it's wrong here
On-demand instances are more expensive.
- ✓
Use Amazon EMR with Spark to convert data to Parquet and store in S3, using spot instances for task nodes.
Why this is correct
Parquet reduces scan size, spot instances reduce cost.
- ✗
Use AWS Glue to convert data to gzip-compressed CSV and query with Athena.
Why it's wrong here
CSV is not optimal for Athena performance.
- ✗
Use Amazon EMR with Hive to transform data to compressed CSV and store in S3.
Why it's wrong here
CSV still incurs full scan costs.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This MLS-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 MLS-C01 exam.