MLS-C01 Data Engineering Practice Question
A company is using AWS Glue to catalog data stored in Amazon S3. The data is partitioned by year, month, day, and hour. The company runs hourly ETL jobs that add new partitions. The Glue crawler is scheduled to run every hour to update the Data Catalog. However, the crawler is taking longer than expected and is not completing before the next crawler run starts. Which action could the company take to resolve this issue?
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 multiple crawlers, each configured to crawl a different path (e.g., one for year=2023, one for year=2024)
Using multiple crawlers to crawl different paths allows parallel processing of partitions, reducing crawler time. Option A is incorrect because the 'Schema updates' option does not increase throughput. Option B is incorrect because partition indexing speeds up queries, not the crawler itself. Option C is incorrect because reducing frequency does not speed up the crawler. Option E is incorrect because AWS Glue does not have a 'Crawler queue' feature; to increase parallelism, you would increase DPUs.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Increase the throughput of the crawler by configuring the 'Schema updates' option
Why it's wrong here
Incorrect. The 'Schema updates' option controls how the crawler handles schema changes, not throughput.
- ✗
Enable partition indexing on the table to speed up the crawler
Why it's wrong here
Incorrect. Partition indexing improves query performance (e.g., for Athena), not crawler speed.
- ✗
Decrease the crawler schedule frequency to every 2 hours to avoid overlapping runs
Why it's wrong here
Incorrect. Decreasing the schedule frequency would increase the backlog and may worsen latency; it does not resolve overlapping runs.
- ✓
Use multiple crawlers, each configured to crawl a different path (e.g., one for year=2023, one for year=2024)
Why this is correct
Correct. Using multiple crawlers configured to crawl different paths (e.g., by year) parallelizes the crawling work, reducing overall time and preventing overlaps.
- ✗
Increase the number of crawler instances by configuring the 'Crawler queue' to process multiple partitions in parallel
Why it's wrong here
Incorrect. AWS Glue does not have a 'Crawler queue' feature to increase crawler instances. This is not a valid configuration option.
Visual reference
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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