MLS-C01 Data Engineering Practice Question
A company uses Amazon Kinesis Data Firehose to deliver streaming data to Amazon S3. The data is in JSON format, and the company wants to convert it to Parquet for efficient querying. Which configuration should be used?
⚠ Common exam trap
Candidates often assume post-processing with AWS Glue (Option B) is the standard approach, overlooking Firehose’s built-in Lambda transformation capability for real-time format conversion, which is more efficient for streaming workloads.
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
✓
Enable data transformation in Firehose using an AWS Lambda function to convert JSON to Parquet, and set the output format to Parquet.
Amazon Kinesis Data Firehose supports data transformation via AWS Lambda, allowing you to convert incoming JSON records to Parquet format before delivery to S3. By enabling a Lambda function to perform the conversion and setting the output format to Parquet, Firehose handles the transformation in-stream, ensuring the data lands in S3 already in the optimized columnar format for efficient querying with services like Amazon Athena or Amazon Redshift Spectrum.
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 data transformation in Firehose using an AWS Lambda function to convert JSON to Parquet, and set the output format to Parquet.
Why this is correct
Firehose can invoke a Lambda function for transformation and write Parquet to S3.
- ✗
Use an AWS Glue job to convert the JSON files in S3 to Parquet after delivery.
Why it's wrong here
This is a batch approach, not real-time, and adds latency.
- ✗
Use Amazon Kinesis Data Analytics to convert the stream to Parquet before sending to Firehose.
Why it's wrong here
Kinesis Data Analytics does not output Parquet format.
- ✗
Configure Firehose to deliver data directly to Amazon Redshift, which automatically converts to Parquet.
Why it's wrong here
Redshift does not automatically convert JSON to Parquet during loading.
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 |
Go deeper
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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