MLS-C01 Data Engineering Practice Question
A media company ingests video metadata from multiple sources into an Amazon S3 bucket. Each metadata record is a JSON file about 2 KB. They use AWS Glue ETL jobs to process these files and load them into Amazon Redshift for analytics. The jobs currently run hourly and take about 10 minutes to process all new files. However, the company is growing and expects the number of files to increase 100x. The data engineering team wants to minimize processing time and cost. The Glue job currently reads all files from the S3 bucket using a full scan. What should they do to optimize the pipeline?
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 S3 event notifications to trigger Glue jobs only for new files
Using S3 event notifications to trigger Glue jobs only for new files eliminates the need to scan all files in the bucket, reducing processing time and cost. Option A consolidating files would reduce the number of small files but does not address the full scan issue and would still require processing all files. Option B converting to Parquet improves performance and reduces scan size, but the job still scans all files unnecessarily. Option C increasing DPUs speeds up processing but increases cost without addressing the root cause of scanning all files.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Consolidate the small JSON files into larger files using a scheduled job
Why it's wrong here
Consolidating files reduces the number of small files but does not eliminate the full scan of all files; the job would still process every consolidated file.
- ✗
Convert the data to Parquet format and partition it
Why it's wrong here
Converting to Parquet improves efficiency and reduces data scanned, but the job would still scan all files in the bucket.
- ✗
Increase the number of Glue DPUs to process files faster
Why it's wrong here
Increasing DPUs speeds up processing but increases cost and does not solve the problem of scanning all files.
- ✓
Use S3 event notifications to trigger Glue jobs only for new files
Why this is correct
S3 event notifications allow the Glue job to be triggered for only new objects, so only new files are processed, eliminating unnecessary full scans.
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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